Techstrong TV January 14, 2026

Hey everyone, welcome back here to another Tech Trunk TV interview. I'm happy to be joined. Well, first timer on our show, new company coming outta stealth.

All exciting, exciting stuff. Say hello to Ido Geffen. Ido was with a company called Novi.

Ido. Welcome, welcome to Text Trunk tv. Thank you.

Very excited to be here, Ellen. So, IDO, we're gonna talk about Novi, we're gonna talk about the stealth coming outta stealth announcement, but let's first talk about ido, tell our, tell our audience a little bit about you. Yeah, sure.

So, uh, my name is Ido. Uh, I'm the CEO and co-founder here at Novi. Uh, 20 years of experience in cyber.

Uh, for the last decade I've been in executive roles in three different cybersecurity startups, and before that I served for 10 years in the Israeli security agency, which is pretty much equivalent to the NSA, uh, mostly leading strategic cyber initiatives. Um, yeah, so this is a briefly about my background in cyber in the, over the last 20 years. So were you in 8,200 or in the, uh, different agency?

Uh, different agency, but pretty much, uh, equivalent. Yeah, we work a lot with a 200. Got it, got it.

No, we've, well, you know, when you cover the cyber market, when 40% of all the cyber VC money is being poured into Israeli cyber startups, you get to know all the different, all the different players and places where, where they're coming from. Um, but you know, that, that's a great thing. So this is your first startup that you founded, though?

Yeah, it is. Yeah. I always like to ask this question of first time founders especially.

Yeah. Because you know, it, you don't wake up one day and say, yeah, I feel like starting a company today. You know, you, it's, you gotta kind of feel it in your, in your gut to, you gotta have that fire, that passion that you, this has to be done.

It, it needs to be done. It's gonna make the world better for you. What, what was that passion?

Er Yeah, what question? So, for many years, uh, gone and er, my two other co-founders gone, by the way, was in eight 200, uh, and er is a program graduate. It was, uh, a team leader in my group in Israeli security agency.

So the three of us are very good friends for a very long time, for more than 15 years. And we always played with this idea that we will, in the end, we will initiate a company together. And September last year, it was the first time that the Open AI released oh one, the first reasoning model.

And we are as a three geek guys, like just read all of the specification card of it and was pretty blown away about the capabilities and, and what we think that could be done with this type of, uh, new type of technology. And we started to connect to, to oh one, the, the, the model, uh, techni, uh, tools that are specifically in, uh, um, tools that we used in the past in order to hack into specific applications, adding our knowledge and techniques into prompts way and, and added in, uh, good. So it's, uh, like a knowledge base that we've added to it.

And we've witnessed that we are very, very quickly being able to do, uh, and find novel issues, novel vulnerabilities and applications. Something that couldn't be done before in automatic way. And this is, was like our aha moment that non something fundamentally changed in the ability of, uh, on how to conduct a penetration testing.

And this, this is the way we felt that this is our moment, is there is a very unique technological shift that we have a very unique expertise and a very big pain that is just going to grow on the, the customer side. The, because the, the, you know, there is much more code now that is generating by ai, much more applications and much more vulnerabilities that you cannot continue and just do it like, like penetration testing is being done today, only point in time in a manual way. Got it.

You know, you know, I've been in security 25, 30 years. When I first started, one of the companies I co-founded, we, we were, one of our products was VM vulnerability assessment of management. And back then, look, it was, uh, it was difficult to get people to at least scan their networks once a year, let alone quarterly, monthly, weekly, continuously.

You know, it to the idea of being able to do that or that you should do it even, you know, it was foreign, was foreign to most people. Now, I remember when, uh, meta Exploit first came out, right? In HD war, I'm sure you've probably have heard of HD and, and everything.

I know HD for a long time, and now we had the ability to do AppSec scanning, penetration testing. But again, it was, it was a tool used by consultants. You would call in maybe a red team or, or something, right?

Again, but once a year to pay, if you were a big PCI, you know, merchant maybe a little or more often, when do you think we, we cross the Rubicon firm once a year or once a quarter to continuous testing? To continuous security scanning? Yeah, so I, I think that, you know, what, what would happen until today is that you have a real technical barrier that you couldn't do this type of testing in continuous way.

Um, and o one of the reasons that you asked also before, you know, when we started to initiate the company, so we spoke with different, uh, CISOs and, and security practitioners, and we got a lot of people that are saying to us, especially in organizations that store sensitive data, and they have, you know, that the, the, the product applications that they're developing is the core revenue making of, of the, of the company that they're telling us we want to, to do much faster, deeper, wider tests. And they told us, for example, that, um, that they want us to do it in, in a daily basis because the, the, the way that Code ships today is in continuous way, right? You have the CICD.

So I think this is the right time for us to, that, to eliminate this pain currently, that really security practitioners need to choose between two bad options, continuous tools that works in continuous way, which is great, but provides very shallow insights and tons of false positives or manual penetration testing that provide novel insights sometimes that it's really just point in time. So at least from what we are feeling today from the market, there is a need and a lot of requests that even not doing the test only once in a month, but can you please connect to our CICD and then we will be able to test the Delta and every new release you will be able to do full blown penetration testing. So I think the, the time is now and, and, and the urgency is just getting bigger because today a developers, you know, utilizing more and more AI tools for developers and you even have vibe coding.

So it's just exploding the, the amount of application that, uh, enterprise today are generating. So I think that this is the right time for it. Agreed.

So I think it was just yesterday, YL Ventures, one of the first Israeli cyber venture funds, pioneered that model, um, released their annual, uh, venture report on the state of Israeli Israeli cyber. You know, it was pretty eye-opening, right? The amount of money, the amount of companies, the amount of exits, serial founders, everything else.

But even in light of that, right? You guys are launching from stealth with a a really, I mean, a seed round. That's pretty remarkable.

Not the biggest ever. I I saw it. You know, they've, lately we've seen some crazy seed rounds, but tell us a little bit about, uh, your seed round here, Novi seed round.

Yeah, so first of all, we were lucky, uh, because Ventures is one of our, it's, uh, the seed investor and also Cannan partner, uh, which is also invested in a lot of, uh, early stage in early stage, early cybersecurity startups like, uh, sny and others. Um, and the fact that we had such a great VC that have a very good experience on, you know, are we in product market fit, and the fact that they've seen that how quickly we were able to generate revenue and dozens of customers, and how quickly we're getting those, this is what, so the, the, it came from them, the, the fact that you should hire, you should raise now much more money in order to, you know, to, to take the advantage that you currently have and, and the pain that is really, uh, vivid today in the market. So you raised the money and congratulations like a $51 million plus seed round, um, beyond it's a lot of money.

What does it mean in terms of accelerating product plans, accelerating go to market for Novi? Yeah, great question. So we understand that in order for us to be one or two, three steps before the bad guys, we need to build something unique with a real moat that it's hard to, for, for, you know, just, uh, you know, for any other attacking group to be in our level.

So the fact that we raised so much money gave us the ability to raise, uh, to, to attract the best talent in the world in cyber, but also in ai, we have PhDs in our team. We have the guy, the head of AI in our team. Dan Padnos was a VP of platform in AI 21.

So he literally built a model that tried to compete with chair GPT for seven years. So this is what gave us the, the confidence that we don't just another wrapper on top of chair GPT, we are building our own proprietary, uh, model that is specialized in Bel. And we already, uh, seen some tremendous results even comparing to Gemini and Claude that for specific types of vulnerability, we already have 55% better results.

And so this type of money and, and the ability to move very fast and to really attract a very unique talent, uh, this is what we think, what give us a good confidence that we will be able to build something that is much, much better than all of the bad guys, uh, and their ability. So we will be faster, deeper, and wider on protecting, uh, our customer. You know, uh, this week actually the 15th, we have our Predict 2026 virtual event.

And, uh, we've got all of the Futura analysts talking, but this is something we spoke about in the cyber session there, which is for 2026 and beyond, just using the frontier models by themselves is not enough to really do security. Right? Right.

Because you gotta remember that those front, those frontier models are as good as the, the information, the data they're trained on, and they're trained on. They don't call 'em large language models for nothing, right? They're large models, but they're not that specialized, right?

Remember that 90% they estimate of all of the data that's digitized is behind firewalls, was not used by these large models to train. And so the future is, you want to call 'em small models, you wanna call 'em, uh, you know, vector databases that are in front, or we're Calling it purpose, purpose trained AI model pur Okay. Purpose trained AI models, right?

That's, that's where the action's gonna be. No one's going to do highly specialized work just on a generic frontier model. Agreed.

Agreed. I, I definitely agree that a lot of the, the challenge also when you're building this type of model is exactly like you described, is ability to create a lot of synthetic data and simulate those type of attacks. Um, and this is exactly what we are doing.

And also those large language models as you described, there are good and in, in everything, right? On how to cook a, a dinner and, and how to answer early generic questions, but they're not specialized in taking Forry knowledge on finding issues at, at, at, uh, at applications, or even more importantly, on how should one fix, mitigate or remediate security issues. Sure.

Um, yeah. So the, of the external context that they're missing, agreed. Um, let's talk about go to market a little bit.

So how, how do people sign up for Novi? How do they get started? What does the cost, you know, what, what's that all look like beyond, beyond the technology?

Yeah, so starting with us, with us is, uh, I'm calling it, we have a pretty no brainer, uh, proposal, meaning that you can just come to our website, Novi security, uh, book for a demo. And, and basically that's it. I mean, after that, signing an MDA and we can start a POV.

And part of the unique proposal that we're saying to people, at least now that we are in the early stages, is you are already paying for penetration testing. You already have budget for it. We are the best penetration testing company in the world, um, so we can do it.

So we, you can replace this budget with us. And by the way, we also can replace your dynamic application security testing, the DAF tools, the vulnerability scanners, um, and we are coming from the outside. So some organizations have external exposure tools, so we can replace the traditional scanners and the manual penetration testing, uh, in one bundle that gives you the best from, from both words.

Um, but really the deployment is just signing an NDA, giving us an access to the application that you liked us to test. And that's it. So this is what makes us move that fast, is the ability to very quick deployment.

And in a matter of less than a week, you're getting an access to the user interface, seeing all of the unique issue that we were able to detect. Um, and most of the time that this is pretty enough for, okay, let's, let's now work together in collaboration. Who, Who would you say the, the average the target customer is?

So we are targeting at least medium size and above organizations. Uh, we're not customers that, or, uh, organizations that are doing penetration testing just for compliance. Those are not our, uh, ideal customer profile.

We really look for organizations that sees themselves as a target, and they really care from the security, uh, of their applications, and they, and they want a prime, uh, results. This is what we are providing. So, Got it.

Ida, we're about outta time, but I wanna make sure we hit this NOV security, N-O-V-E-E Security. Sure. Yeah, if you Can go sign up and start, you know, as you said, sign it in, DA, and get a, uh, a, uh, a, an instant going and see how it goes.

Yeah, definitely. Excellent. It's, uh, How we Mu congratulations, you know, mazel tough on the, on the raises and good luck going to market now.

Right now it gets fun. Yeah. Yeah, it is.

Now, now they game me on. Definitely. All right.

Ada Geffen, CEO co-founder at Novi at Novi Security, continuous AI powered, uh, pen testing and more all your security testing right in one place. We're, we're gonna take a break here on text on tv. We'll be right back.

ai Leadership Insight series. I'm your host, Mike Baard. Today we're with Alex Victoria, who's CTO for Zen Business, and we're talking about, well, how AI will be applied to small businesses and how it can maybe help them compete more effectively against the big guys.

Alex, welcome the show. Thanks for having me, Mike. Good to meet you.

So maybe level set us a little bit here first, but what is fundamentally different about using AI in the context of a small business versus what we might have seen in these larger enterprises where there's a lot more resources? What do they need to do to kind of turn AI on and actually, you know, leverage this? Yeah, there's really two, um, two different ways I think about it.

For, for Zen Business, our goal is to really, uh, help very small businesses get up and running and get started from the beginning. And a lot of our customers are first time business beginners. Um, and that, that, that journey is a complex one where you, you run into to many, many different complex questions throughout the beginning of the process, but even after you've got your business up and running, there's a constant kind of barrage of work that the, the, the entrepreneur never thought they would have to do.

You know, a lot of these folks thought they were gonna get to do a side gig with their dream, but instead they spend 70% of their time making sure their accounting books are correct. Uh, and so, you know, Zen Business has always, even before this AI boom, been focused on that problem. Uh, and so what we're really trying to do is leverage AI to get, to make all that easier for the small businesses to get started faster.

The second way I think about it is, how are small businesses going to leverage AI to deliver their products to their customers? And that's not so much what we're focused on at the moment. Um, although I really do think that's where we head in the long run, is that we start using something like Velo.

Our, our personal AI assistant for small businesses. We like to think of Velo as kind of like their co-founder, productivity partner. Um, I could see in the future where they're using velo to like, operate things inside of their business as well, um, or, or other AI platforms.

So it's really, it's really, um, either of those, our focus today is really on, on them operating the business. Alright. Well you mentioned Velo.

So yeah, for the uninitiated, what is Velo exactly? So Velo is, you know, our vision with Velo is that it's the productivity partner, co-founder for the small business. And then it begins your, with your journey, uh, from the day you start interacting with Zen business.

So the majority of our customers are people who are al either already working or already have a business that are starting a new one. And so they'll find us by way of Google or something like that. From that moment we have Velos sitting there with them, uh, helping them research.

So the other thing is a lot of customers will spend sometimes months researching what to do with their LLC, what state to put it in, whether they need a DBA or not, what accounting software they should use, what their website should be. There's a lot of these questions that they have to answer. And a lot of times they're using sources from all over the internet, jumping around and doing all this research maniacally.

'cause it's scary. It's a scary decision to get a business started, especially when you've never done it before. And so the idea from when you get the Zen Business Velo is there from the beginning, you can, you can use Velo for free and you can research all the different options of your business, uh, needs before you get started, right on Zen business.

And then it follows them down the journey so they can create an account with Velo and use it for free just to do research. We'll, even one of the things Velo does is it'll even tell you who our competitors are and why you might wanna pick one or the other. The idea is to really just, uh, help the consumer make the right call.

And of course, we want them to choose us 'cause we think we're the right call. Um, but we wanna be honest with them too. Uh, the next step from there is if they actually decide to start with Zen Business, then they end up with a full account and velo.

But at each, each one of those steps throughout the way, Velo is learning more and more about them, their desires and what they wanna accomplish, so that by the time they're up and running, it's got all the context already. And that's, that's allowing us to do things like, say, you need to file an EIN Velo can fill the form for you because it knows so much about your business already. Uh, and, and that's just one example of what's coming in the next couple weeks.

But there will be a long line of these, like all this kind of operational filing stuff, your annual reports, all the things you have to do around kind of keeping your business compliant with the state. Uh, VE Velo is gonna be able to do most of that for you. Um, and today, today the customer has to go click like through a 30 page form filler and enter all these complex details to get these things done.

But by the time they've getting gotten to the point through us, we have collected all that context and can make things, these things happen faster for them. Um, so, you know, velo, like when a tax season's coming around, Velo reaches out and says, Hey, it's tax season time. I know that you own an Italian restaurant in Austin, Texas, and you've, your annual reports are due on this date.

And you have, because I have access to your accounting software, I can tell you what your next steps are on getting your taxes prepped and all that kind of stuff. So will it generate the annual report that I might not need to file for the small business based on what it knows about me? Or how far will it go?

Well, today, it's, it's not gonna get, you're, you're gonna have to tell it to finish. You know, it's not just gonna go do it, I don't think just yet. Um, but in a lot of cases, you know, the backend of our filing systems are automated as well.

So we, we do foresee a point where velo could just know its annual report season, prepare your annual report, send you a note and say, come hit okay on it. Uh, and, and the thing is, annual reports are quite different in every state. So some do them in different, they have different purposes and at different times of the year.

Um, but it could certainly have it ready for you. And when you say, okay, then automation on our backend is also, uh, doing it quickly for you. And so that's the vision is that, um, in this space, we've, we've been challenged with combining technology and, and people and AI has become this, this thing that is allowing us to do it more effectively.

Uh, and it's, it's, it's just turning up the automation opportunities to the roof for us. And then what we're learning is how to inf help our customers. You know, the next step is like, how to figure out how to get them to do it too.

I truly, personally believe that like the small business is probably the primary way for the average am average American or average person to get their piece of the AI boom. You know, I don't want to get like philosophical, but you know, a lot of wealth is accumulating in, in, in a small number of places. Um, I actually think this is a better time than any for people to start a small business because they're gonna get to use AI to make it more effective for their customers.

So it's an exciting time to, to be where we are. We've been slogging at this for seven years and it's, it's all of a sudden, uh, I think we're at the point where we can actually achieve our dream, which is the, is to be the most effective as possible to help our customers make this decision to get started. 'cause it's a scary one.

And we believe in entrepreneurship and everybody having a chance to be their own boss. What's behind the platform exactly. Is because I don't think, did you build your own foundation model?

Seems unlikely. So what is No, you guys working with here and how does it Yeah, what come together? What I tell it's funny, people ask that, and I tell 'em investors, I'm like, well, if you gimme a couple billion dollars, you know, I'll go, I'll go make a model if you really want us to differentiate.

Um, but no, we don't need to do that. In fact, velo velo itself is a, a fairly common public pattern that we've written about on our tech blog as well. Um, it's a, it's an, um, a coalition of routers, a agent, a coalition of agents within a routing agent that, that decides how to answer questions or do tasks for a customer.

Each of those is dependent on, uh, prompts and a bunch of tools. So what makes Velo different for us is that it has our knowledge base, which is really every detail of everything a small business would need to know in all 50 states. Plus, uh, it has access to our tools, which are all the different platform APIs we apply.

So we have your website, bank account, domain names, uh, uh, accounting software, and then all the compliance and formations needs as well. Uh, and so all those put together, uh, allows us to do this. Um, the model part is interesting.

So one of the things we did early on was we decided to centralize LLM usage in our platform. And so we have a central part of the Zen business platform that obfuscates the details of the different providers. So we use Google, we use OpenAI, we use Anthropic depending on the task, and, um, we can change those on the fly if needed.

Um, and we've had to do that, like all of a sudden Gemini has a problem. We switch it all over to OpenAI as a back a backup thing that we wrote about that on our, our tech blog as well. But another crafty thing we've done, 'cause people get concerned about the cost, is we use the, we use very old small models.

So like we're using the Gemini two oh flash for like, most of what we do. And then what we do is when there's a, when there's a certain case that just needs the additional logic, we can upgrade it to like, say, go use OpenAI four oh or whatever. But we, we, we avoid the, the biggest, most effective, most expensive models, kind of like the plague.

And what we're finding is, you know, for most of what we need to do, we don't, we don't need them. So we like the ability of not being locked into one vendor. We can switch back and forth and, and honestly, they all, they all are producing really amazing technology that it works, you know, it's with none of this would work.

The real, the real, the real thing we learned was that tool calling the model has to be good at calling tools and, and we solve a lot of problems with tool calling. Do you think as we go along that, um, small businesses typically interact with other small businesses, and if we're all gonna have our own AI tools and AI agents at some point, you know, does my AI call your AI to complete a task as a small business? Or how does that play out in your mind?

I mean, I think we'll inch towards that. Uh, it's funny, I think of years, even, even when this all started, like a year or two, a couple years ago, we were like, pretty soon recruiting is just gonna be like, you know, the, the hiring persons AI talks to the candidates ai, and they just, they make a decision. I don't think we're there yet.

Um, I certainly think AI can facilitate the communication between the two. That's like a no-brainer use case today. And that, that's actually where most of the real value I've seen is coming from these AI products is like customer service.

You know, that, that it's things that are heavily, uh, layered of upon people talking to each other can be facilitated by ai. So I could see AI going, you're about to do a deal with so and so, and we're gonna redline the contract and back and forth it between two ais and present it to both of you at the end and say, this is, this matches both of your needs. Like hit hit okay to go.

Mm-hmm. Um, we, I, you know, that's, that's, that's, that's here we could be able to do that today if, if someone wanted to. Do you think small businesses are prepared for this scenario, though?

'cause at some point their customers will also have AI agents. Yeah. And those AI agents will be optimized to maybe buy something at the lowest cost possible, and your AI agent is optimized to sell it as the most profitable way possible, and the two of them will battle it out somewhere in the ether.

Yeah. I mean, I guess supply and demand, that's like the, the purest form of supply and demand curve is mm-hmm. Two algorithms go until they find the happy point and go.

Um, yeah, I, I think certainly it could be facilitated by that. Um, it, it's a, you know, we found that like a lot of our customers, the ones who aren't in technology businesses, uh, managing all this stuff is quite complex. I mean, e even even for like, you know, entering your expenses and having the time to even go log into something every day and make sure you uploaded your receipts for your, uh, for your expenses, that, that, that's challenging for a lot of the folks.

And so I do think there's gonna be some work to figure out how to make them able to use this technology because it's, it's pretty complex today. I mean, we we're lucky to have a, a bunch of really smart, uh, product development people at Zen Business, um, and, and, you know, Google and Anthropic and those guys have everybody else. So I, I don't know how the, you know, right now, the average small business that doesn't know how to wield this stuff is, it's gonna be hard to figure out.

So that's where I think there's an opportunity for us in the future and somebody else to help. I also think, you know, all those engineers that people say are having trouble getting jobs, I think they, they have a lot of value if they know how to wield this technology. Um, I was telling my nephew who just gradua is graduating from college this year with a CS degree, I was like, you know, if you learn how to use this stuff, you're gonna be really valuable.

You know, so, because I think it's pretty hard to be getting a job right now, and Well, to that point in the societal impact, right? So we're seeing it's harder for, uh, new people to get hired into a space than ever. It doesn't matter what the vertical is these days.

And we're also seeing more folks get laid off because companies are thinking they're gonna automate certain things that they used to hire people to do. But does that create a larger pool from which we will see more small businesses start to emerge and people will be able to engage in that activity because the complexity of starting a business is dropping? Yeah.

And that, I, I agree with that completely. Um, I think, well, one thing I don't, I don't necessarily think they're all getting laid off because of ai. I think maybe they overhired and there's just a reckoning happening.

Um, but there, I do think that, uh, that's gonna be a way for people to benefit from all this, and it's gonna be easier than ever. And, and honestly, when we started Zen Business, one of, one of the ideas was that, uh, the, the barrier of entry for starting a business is lowering because of technology. And particularly at that time, it was kind of SaaS technology.

You don't need the firm anymore to get a business started. You don't need to hire 10 people. You could get online and start taking money and put a product together and sell it.

And you could do that all yourself with technology, AI is like the next evolution of that, where, I mean, you could build your, your product with cloud code if you, if you knew how to wield that thing a little bit. And that's why I think, I think, you know, I, I'm very passionate about those agentic development tools. They work and, uh, people should be committed to using them.

We use them a lot. Um, they still require a technology person to run 'em though, you know? Mm-hmm.

And I, and I think that's gonna be the case. And I, uh, one of the ways engineers can get a lot of value in their careers too, is learning how you still need to know how to build software ultimately to build something complex, you know? So do you think small business owners will develop something that feels like a relationship with these AI agents and maybe even give 'em the name?

Or are they gonna be more, you know, seen as disposable kind of software widgets and we're not gonna get that emotionally attached to them? That, that's an interesting idea. I'm trying to think of, the way I use, the way I use Chad GBT is I have, I have like dialed that thing in to, to be like, really, um, personalized to the way I like to communicate when I'm using the voice mode.

And I, I, you know, I, I don't want any fluffy language. I've come up with all these prompts that make it say as little as humanly possible, and it just treat, I want, I'm like, I want you to treat me like a robot. Just like, say things you know, don't.

And, uh, and then I even picked the voice and one day I was using it, my wife was like, did you ever notice the voice you chose? Sounds like me. I was like, I don't know.

Mm-hmm. I, maybe I did. I don't, I didn't do that on purpose.

But yeah, I think people are gonna wanna personalize their experience if, especially if they're com communicating with voice, which is right around the corner for us. Uh, we're, we're gonna enable that sometime soon. And I think a lot more and more people are talking to these things.

I think you're gonna want it to kind of know who you are and know how you like to communicate and probably give it a name. I mean, I would, I'd, I'd, I'd love to high if it was running my business for me, I'd be high fiving it. Like, if I could high five cloud code, I would code, yeah.

Hot code's. Amazing. Well, maybe, you know, you're gonna do what the agent says you should do, because it sounds like somebody you're already listening to, right?

Well, yeah, there's, there's a lot of like, futurist thinkers saying, agentic CEOs are around the corner. So I could see a world where you've created your own agent to just kind of manage you day to day, and you're just doing what it tells you. But of course, you created it.

There you go. If you don't like it, you can veto it. Yeah.

Um, so as you look into 2026, you know, it's a new year, what are you excited about? What do you think we're gonna see next? Well, I mean, for Zen business, you know, like I said, we've always been in this spot of just trying to make it easy to get your business up and running and then run it.

Focus on what you love to do and make some money and be your own boss. Uh, I think for the first time, velo, you know, having the technology in place to deliver velo throughout that experience is the most exciting thing I've, uh, I've, I have going for me. Um, you know, and then also when we started Velo, we really made the choice to, to kind of learn in, in public and write about it on our tech blogs.

So, uh, I'm, I'm excited about, you know, showing off the talent we have in the team, but also giving back to the folks that, you know, put some of these things in place to get us up and running. And maybe, you know, some of our customers learn from it too, uh, and I think, uh, we're gonna, we're gonna really accelerate what we can do. The other, the other learning that we've had is, like, our velo team has only been around for a couple months, and when you know how to leverage this technology in the right way, they've, they've delivered at a rate that is way higher than traditional engineering teams.

And so I think we're gonna see an extremely fast pace, like feature roadmap, you know, Avela iss gonna do more and more and more and more every day as we continue to focus on it. And, and, you know, that's probably true of anybody who's building an age agent system like this. So, in terms of like the macro view, we're gonna get a lot of software.

You know, we built, we have this internal system. We built a very complex management UI for it with, with cloud code, and, uh, you know, with automating engineering pipelines. And of course I had to like, take care of it, but the thing it built was so complicated, it actually made me think like, do we really need to build this?

And I think that's the world where getting into, like, you can literally build anything you can think of. And if you can, and you can do it with a low number of resources, except you gotta pay anthropic, open AI or Google, uh, and, and your maybe open source models get to a point where you can just use 'em to do it too. But if you can build anything you want, I think that's pretty exciting world.

You know, like, yeah. So I, I think it's gonna produce some cool companies and cool businesses small and large. Alright, well folks you're hearing in here, Hey, if you're outta work or you're just playing fed up with your existing job, go start your own company.

'cause it's gonna be a lot easier to do than ever. Hey Alex, thanks for being on the show. Yeah, thanks for having me.

All right. And thank you all for watching the latest episode of the Techstrong AI Leadership Insight series. You can find this episode and others on our website and invite you to check them all out.

And until then, we'll see you next time. Hey everyone, welcome to Still Cyber. I'm Alan Shimel.

And I'm Mitch Ashley. And we've been doing this a while. Still.

Cyber Baby, still Cyber Mitch, it's good to see you. Happy New Year, man. Happy New Year.

And, uh, you know, chalking up another circle around the sun and, uh, we're podcasting it still, So still it's awesome. Still, still cyber still podcasting. Hey, I wanna welcome our guest for this, uh, episode of Still Cyber.

Her name is, or slo, uh, or is an analyst with YL Ventures, or welcome to Still Cyber. It's great to have you on here. It's great to be here.

Ellen and Mitch, thank you for having me. Thanks for joining us. Appreciate it.

Yeah. Um, or before we jump into stuff, if you don't mind, give people a little bit kind of, of your background, your journey to being an analyst with ell, and though I look, I, I remember when Y first started ell to tell you the truth. Mm-hmm.

Yeah. Um, you know, Mitch, you hired that old, but for people maybe don't know why, maybe you can give them a quick recap of that as well. Yeah, for sure.

I I'll start for, uh, for my background. So, uh, so I'm an analyst at 12 Ventures in the past, uh, two years. Uh, I live in Tel Aviv, uh, like, uh, all of the cybersecurity tech people here in Israel, right?

Mm-hmm. Um, so prior to that, I served in the 8,200 unit. Um, then I operated in several startups, uh, here in Israel, uh, as a security research security.

I held security research, security analyst, uh, positions. The last role was in the incident response department at Signia Signia Consulting. Uh, it's a company providing incident response, uh, service services, uh, I assume you've heard about it, but not in a best context in the past, uh, in the past couple.

Yeah, yes. Offensive security and stuff like this. Yes.

Yeah. And, um, uh, it's, it's an amazing company, uh, which exposed me to, uh, the recent, uh, trends and attacks, uh, right. Uh, companies are coming to, uh, to respond to incidents where the security stack failed to perform.

So I was in this, uh, interesting interject, interjection, sorry. Um, and yeah, I kind of did the shift left, uh, in my career when, uh, when I chose to join Wild Ventures to see where the magic, uh, begins, uh, to invest, absolutely. Invest in early stage cybersecurity.

Yes. Well, So the, the YL ventures, if you don't mind me jumping in mm-hmm. Really sort of pioneered the, the model of investing in early stages, Israeli based companies Yeah.

With an eye towards helping them migrate or penetrate the North American, European, you know, rest of world market. And oftentimes that meant that at some point, some of the executives, maybe the sales and marketing team would, would be based in the us whether it was Boston or, or, or Silicon Valley or what have you. But r and d engineering research usually stayed in Israel.

And that's something one of the very popular model, Very successful first, very, if it's successful theme based, um, yeah. Venture funds centered around that as well as Security. Yeah.

So, yeah. So, so also security always. Yeah.

Yeah. So, so, uh, so, so what you described, uh, really relates to, to well ventures and how, how we operate. So well, ventures been around since 2007.

Uh, we're, uh, uh, top Israeli cybersecurity, uh, uh, vc, uh, in Israel. Uh, we invest, uh, early stage, uh, seed investments in cybersecurity, as you said, uh, Israeli entrepreneurs, uh, only, uh, we're investing from our fifth fund, uh, now, which is, uh, $450 million. Uh, and, uh, what, what, what our expertise, what we bring to the table is our value add, uh, um, uh, program, which is, uh, here in Israel, we are responsible for investments and deal flow and, and, and pursuing new investments, but also supporting companies, uh, sends the minute they get their, the, the check, they, they, they put the money in the bank.

So we support them in, in product market feed, in marketing, in in hr, recruitments in operations, everything they need here in Israel. And also we have, um, uh, uh, sites in San Francisco and in New York also that are responsible for this exact, uh, business development and to keep nurturing our, uh, uh, great network of advisors, security practitioners that help us and advise us and our portfolio also. So the model of, of, of a typical, uh, cybersecurity startup also applied, uh, to us where the, the development and, and, and, and r and d sort of is here in Israel.

And the, the business and the sales is in the US also. Excellent. Yeah.

So, Or you know, it, it's a great model and Vin the team has done, have done an amazing job. We wanted to talk today though, about this report that just came out. Mm-hmm.

Right? Um, kind of, and this is not the first year, I don't know how many years, why else doing it. Uh, maybe you would know, but it, it's kind of A, this is the 10th edition, Alex, the 10th edition.

It's been a while. My God, 10th Edition. Yeah.

And it's kind of the state of the Israeli cyber investment scene, if you will. Yeah, Yeah. Venture scene.

Yeah. Um, people can get it from the YL venture site if they go. Mm-hmm.

We don't have to dive really deep, deep, deep, but give us kind of the highlights, if you will. Yeah, for sure. So, so as you mentioned, uh, the report is called, uh, the State of the Cyber Nation.

Uh, so basically we, we've been collecting data throughout the entire year, and we released a report in the, in January of the following year to provide the most holistic view on how, what happened in Israel in cybersecurity in the past, uh, year. Uh, we collect data up until the very last minute of the very last day of the, of the previous year, because I don't know if you've noticed, but December was, uh, was crazy in, in terms of funding and MNAs in Israel. So, uh, the ecosystem never rests, not even in No, uh, in, uh, holidays, in US holidays, Uhhuh.

Um, so yeah, we collect the data, our position in the very core of the cybersecurity ecosystem exposes to, uh, to, to everything. And we are able to provide the most accurate numbers and also insights and our projections for the following year. Um, so yeah, let's, let's talk about it.

Yeah. It's the 10th edition. And, and, you know, I I I, I've been living in the data in, in the past, uh, weeks and, um, and, and so, um, um, you think that you have, that, you have a gasp of, of that the ecosystem.

You, you get it, figure it out, and you know what's coming and what happened. And the numbers surprised even myself in, in the best way possible. Um, this was the most active year in Israel, uh, in terms of funding and, and, and money entering here.

1 billion, uh, entering Israel, uh, over 136, uh, rounds. Uh, which is the most rounds we've seen in the past decade. This is amazing.

And also, uh, we talked about it, uh, before that, uh, uh, 40% of all cybersecurity funding in the world, uh, was invested in Israel. And when, when you look at, at, at the map of the world, Israel is, it's like a dot of dirt. Like w we are so small.

We are so small. So this is absolutely incredible. Uh, and I'm so grateful to be part of it.

Um, and, and we Can, you know, one of the metrics or that that Yeah. I saw in the report, and we were talking off camera that I think really capture it is yeah, 40%, and if I'm wrong, correct me, 40% of all of the venture capital invested into cyber companies in 2025 went to Israeli based cyber companies. That's amazing.

That's unbelievable. Right? A country to start size approximately of the state of New Jersey here in the us Right.

40 40, nearly half of all the cyber funding in the world. Yeah, Ellen. And, you know, I think, I think, uh, our size is also our biggest trend.

Uh, 'cause we talked about a little bit about, uh, why this is happening. How are, how is Israel so strong, uh, in cybersecurity and why everyone are so eager to start their own companies and, and also are able to succeed and, and create category leading companies in cybersecurity. So, um, uh, I I, I, I welcome you to, to come to Israel and, and walk the streets of the Tel Aviv and see the magic happens.

Yeah. No, I've been there five or six times. I, I, I'm well aware.

Um, and I have so many, so many friends, not just actually in the cyber market, the cyberspace in Israel, but the, the DevOps community there. My friend Zeman runs the DevOps Tel Aviv DevOps community. It's also a vibrant, vibrant, rich community.

Yeah. Not as much as the cyber. Um, but you know, Mitch looking at one metric, the investment, the VC investment mm-hmm.

Let's call that money in, but also gotta look at money out. What if like, the exits this year, right? Well, you have The Wiz is a $30 billion, was it 32 or $36 billion?

32, I believe. Yeah, 30, yeah. Exit.

So that's certainly a, it's kind of a gravity, well, a gravity sinks that, that kind of brings it up. But it's not just the wiz, how many, and I, I believe it's in the report or mm-hmm. How many exits or liquidity events, uh, also in the, in this past year from Israeli based cybersecurity companies that were, you know, involved in m and a, uh, activity.

Yeah. Yeah. So, so we've seen a lot of exits also.

And, and what's also surprising in, in this m and a activity in, in 2025, a trend that we've seen starting, uh, last year and and has been accelerating this year is, is the fact that, uh, Israeli cybersecurity startups are acquiring other Israeli cybersecurity startups, like consolidation within our ecosystem. So this, this represents, uh, I think like, um, um, a mature and independent market. Uh, you've seen companies like Cato Networks that acquired, uh, aim Security, our company, this was our com portfolio company, aim, security, security for a, a company, uh, got acquired by Cato this year.

Um, yes, Sierra that acquired also a Israeli company, uh, Sandino, one that acquired from security, like big category leaders that choose to, to acquire Israeli startups within the ecosystem. Uh, we haven't seen, uh, uh, a lot of, of those activities in the past. And now in 2025, we've seen 12 of those acquisitions.

Um, I think that's, to go back to the, to go back to, uh, to what we talked about earlier with, um, this is a proven market. This is no longer the, the startup nation. We're the, the scale up nation.

Uh, everybody, uh, believe they can build the next wheel, the next Sierra, the next armies. Um, so, uh, there is also an ecosystem of, uh, second time entrepreneurs or, or serial entrepreneurs that are investing in new entrepreneurs, mentoring them. Uh, this is a, like a cycle and never ends of, of, of nurturing and mentoring, uh, older entrepreneurs, new to new entrepreneurs.

This is what fuels this ecosystem. And also the proven, uh, exits, right. With armies, uh, CyberArk.

Yeah. CyberArk also is this year mm-hmm. Plus arm.

Mm-hmm. That's a good point. Yeah.

Yeah. Um, you know, we, first of all, look, I encourage anyone watching or listening to this go, go download the report. See for yourself, the numbers are pretty, for sure, eye popping.

But let, let's go beyond the numbers. Why, why, you know, look, the whole, you, you could say the whole idea of how Israel was founded as a modern country, country, not company, a country in 1948 was a bit of a miracle in itself. Right?

There's a whole story, there's movies about it and everything else, but it, there really, there's a method. There's a, there, there are several reasons why. Yeah.

I think we, we see the Israeli cyber market cyst at ecosystem community be so strong. Mm-hmm. And it, I I think it, you mentioned your former 8,200.

Yeah. And I have to apologize, is there a unit 8,100 in cyber two, or is it just 8,200? There is a 8,200 unit, and there is also your unit called 81.

Right? Eight one. Okay.

Eight one. Okay. We, we, I've met People from both.

Yes. Yeah. Okay.

And that's why I always get confused, but you know, for those who look, most people I think in the cyber world have heard of it. For those who haven't, it's, it's kind of the Israeli version of the NSA, if you will. Mm-hmm.

Here we have the National Security Agency, uh, but you know, it's a cyber unit that's responsible for both offensive and defensive mm-hmm. Cyber operations, and, you know, and the, and the IDF has a world renowned reputation for being one of the best, not the best when, when it comes to cyber. So, you know, a lot of, a lot of the Israeli cyber talent comes out of those, those units.

Yeah, For sure. However, That's not unique to Israel, right. We have the NSA here and the NSA's big, there's a lot.

Mm-hmm. The NSA has a big budget. There's some of the smartest people in the world.

I know, you know, I've, Mitchell and I have been to Fort Meat. Mm-hmm. And, uh, you know, we, we know the kind of people there, but not just the us European nations, uh, Asian nations.

Every nation today has to have a cyber unit, right? Mm-hmm. And, and, and a lot of these nations are a lot bigger, have more budget, have more people.

Yeah. What is it about the 8,200 or the IDF system or the Israeli culture, or what is it that Yeah. Has helped you sort?

I think it's come Together. It's all combined. It's all combined, right.

You know, uh, the, the usually mental mentality we are, uh, restless. Uh, no, but, but, uh, jokes, joke aside, I think that, um, I think that the, the mentality in the 8,200, uh, unit in those cyber units, um, is that there is nothing you can do. Uh, we are, uh, we're in a, in a complicated, uh, uh, geopolitical area, right.

Uh, to be gentle. Mm-hmm. And, uh, we need to, to protect ourselves, and we need to, to, to innovate and find ways to do that.

So the innovation and the, the innovation mentality starts as early as, uh, in the army, uh, where you, you need to find ways to, to, to innovate and, and to be the best and, and to protect yourself. And this mentality, uh, you, you live the, the army with, with this, uh, can do approach. I can do anything.

I have the resources to do that. Um, and we talked about earlier about, um, this ecosystem that is, uh, very, uh, nurturing, uh, uh, older entrepreneurs are mentoring and investing in, in new entrepreneurs. Um, and also, uh, everyone, uh, wants to be, uh, the next tweet we talked about that.

I think another aspect that is interesting to see, um, uh, also, uh, a rising trend that I, I'd love to, to dig deeper into, is that, um, is the global VCs dominance in 2025, we've seen global VCs, uh, investing in cybersecurity in Israel, uh, as soon as seed stages. This is the first year that global VCs are invested more than Israeli VCs, um, in cybersecurity. Um, uh, so, so the, the majority of the money is global, uh, that entered, that invested in cybersecurity in Israel this year.

Um, yeah, No, this is a change. You're right. Because, you know, originally y and of a handful of Israelis kind of had the inside track on all of these great new, you know, all the people coming outta, like you would think they were camped out in big cars outside the exit to 82.

Right. To 8,200 as they come out, you're writing checks and having them start. But no, every now it's not just the YL and the other Israeli based funds.

Yeah. It's a fundamental change. Yeah.

I, it's started, I remember I had a chance to meet the founders of Aramis Aramis, um, at an insight partners, uh, uh, uh, insight Ventures mm-hmm. Uh, event in, in Iceland before COVID years ago. And at the time, insight had just bought an Israeli based company to help them do Israeli based cyber well, all Israeli based venture, but they're not even buying the Israeli companies.

Every global VC now has an office in Tel Aviv. Yeah. Or Herz Leah.

Right? Yeah. And, and, and so what did, it makes it a little harder for y doesn't it, a lot more competition.

Mm-hmm. So, so yeah. So, so global VCs have been around, uh, always been around, but they, they, they used to invest in, in cyber in later stages.

Later, Yeah, Later stages. So the, the, the change here that is, they're writing checks now for, uh, two entrepreneurs with a presentation, like the seed stages, our stages. Mm-hmm.

Like the, the expertise of, of wild. Um, I think that it, it, it is a, it is an amazing change and it's, it's, it's great that money keeps, uh, keeps entering here and investing in Israeli cybersecurity entrepreneurs. Uh, we, this led us to adopt, um, uh, a, a split seed model that we've seen, uh, rising in the past couple of years.

And I believe it'll keep, keep accelerating, uh, a model where, uh, uh, seed stage cybersecurity com, uh, uh, venture capital such as Wild Ventures is co co-investing with, uh, top tier global VCs in seed stage. So the entrepreneurs, the entrepreneurs get like the best of both world. They get our expertise of the help of we understand the Israeli mentality and we help them, uh, build their company since day one.

And they also get, um, uh, a global, uh, VC invested in seed stage that is also also minded for later stages. Um, so they get the best of both, both world and, and we are not, uh, afraid that this will, um, this, that this will hurt our investments because, uh, we're experts in building companies, uh, from from day one here in Israel, and entrepreneurs understand our value. So the split seed also, it's an accelerator for them.

So we've seen it in the next, in the past couple of years. And, and it'll just keep, keep on growing, I believe. I agree.

It also makes for bigger seed rounds, right? Yeah. I recently interviewed an Israeli company, I'm trying to remember.

I don't remember the name, but it was like an 80 something million dollars seed round or something like that. Right? It it's nuts.

I mean, Yeah. Another, those seeds Are, needs to be, yeah, they're not three, four, I mean, a good a seed round, $4 million was a good seed round. Mm-hmm.

Right? Yeah. It kept you a ke it'll fund you for 18 months and, you know, 80 million nuts.

Um, but you know what? So, or there are, there, there's 8,200, there's the Israeli entrepreneurial character in, in, you know, wanting to experiment and, and do things. There's this environment of serial entrepreneurs and second, second growth, third growth companies.

Yeah. But there's something else. And Mitch, I, I'd love to hear you chime in on this, which is, I think what we see, what we saw in 2025 in the Israeli cyber scene is for foretelling what we're gonna see in the world cyber scene in 2026 and and beyond, which is for a long time we heard, where's the innovation?

Where's the innovation? Where's what's new in security? Well, we, we're now seeing what's new in security.

It's security, having the secure AI generated code, it's security having to defend against AI generated threats. It's security using ai Yeah. To be more effective security.

I think this is going to lead to increased budgets for companies buying security. It's gonna lead to more security, innovation, and security vendors doing new things. It'll set off more m and a, more liquidity, more investment.

Mitch, you speak to a lot of companies. What do you think I do, and I wanted to share with you, or that, um, we're just getting ready to launch our next update to our, our buyer decision maker data. And mm-hmm.

For the first time, AI is act. One of the things we ask is, uh, what are your plans for investing, either increasing significantly or slightly, or stay the same, reduce across the number of technologies. AI in development is the top, top of the list, followed by security.

Um, yeah. Security's always up at the top. Um, so for the first time, AI is, AI is kind of in the significant category, so people are ramping up dollars.

So that, that creates a wide open, if not a field that you're already pursuing, of course, whether it's code security or ai, agent control planes and the environment mm-hmm. That they work in and security guardrails. You, you have such a even bigger, wide open new field to play in as well as traditional security.

What's your perspective on that? Yeah, so, so, uh, we must talk about ai, right? I, I heard someone says that, uh, this is the greatest, uh, uh, uh, revolution since the, the beginning of, of computers.

Um, it's, it's not a bubble. It's not going anywhere, and it's just, uh, gonna accelerate and, and in our times, first come the technology and then come the security, right? So we're in this, this area where the technology, and then we're building the security on top of it.

So, um, so, so yeah, for sure. So, security for ai, uh, was one of the, uh, of the top, uh, top leading trends, hot, hot spaces in, in cybersecurity in 2025. Um, um, where, where we've seen, uh, lots of, of new startups, uh, rising.

So if in the, the first wave of those security for AI companies, we saw companies like aim, security, our company, uh, prompt security, lasso security, that they, that are security securing, uh, the use in ai, uh, uh, uh, incorporate corporate use of AI if it's, uh, uh, to GPT or, or, or whatever, from prompt injections, from data leakage, um, basically securing, uh, AI responding to human input. Now, there is a new wave of security for ai, which is securing, um, uh, the, the, and governing, uh, the, the use of, of AI agents that are operating within your environment. They're, they're particularly autonomous employees that are accessing data.

They have permissions. They, they are, um, they have access to assets. They, they do tasks, uh, on behalf of employees.

And, and then you need to, a way to find a way to govern it and control it. Um, yeah, we are moving to, to an area where, uh, employees are, the, the tasks of employees are, are AI generated and human led. Uh, and you need to find a way to, to govern it and control it.

Agree. And we're kind of creating sort of an open, wide open field of everybody using AI before we've really, truly feel like we've secured it while we're putting the new securities and measures in place that You're talking about. For sure.

Because it, it, it has so many, so many advantages like making, uh, uh, creating super employees, empowering employees, and making work much more efficient. Uh, you can do much more work, uh, in, in the same, in the same resources. And we also see it in, in security, right?

We've talked about, uh, AI enabling, uh, security, and we, we've seen also that in 20, 25 companies that use AI for better security solutions. And we will keep seeing that in the future also. Yeah.

I, I, you know, we're, we're running low on time, but I mean, suffice to say this is a rising tide. Mm-hmm. Mm-hmm.

That's gonna lift all boats, not just the Israeli cyber scene Yeah. But all the cybers. But when you already have that as it's almost a follow on wave to the momentum that's been building Yeah.

In the Israeli cyber scene. It, I think it's going to, I I can't wait to talk about the 2026 report. Yeah, me too.

That'll be interesting. For sure. Yeah, me too.

And, and you can see that, um, that, uh, that the Israeli, uh, cybersecurity ecosystem, we survived pandemic, and we survived war, and we, we survived, uh, instability. If I, if I being gentle and we keep seeing, uh, we, we're not just surviving those years, we're accelerating, Thriving, yeah. Mm-hmm.

Thriving. Yeah, exactly. So this give you a sense of, of the cybersecurity, uh, ecosystem mentality.

Uh, and, and I understand global VCs wanting, in wanting to, to get a bite of that. Absolutely. Yeah.

Or, you know, what we didn't mention for people want to download the report at Y Ventures. What's the website? Uh, yes.

com. Just access it and be easy. Yeah.

Hey, thanks for being on Still Cyber with Mitch and I continued success to you, to yo to the Y team. Uh, we always watch we're fans. And you have an invitation for the 2026 report.

Yeah. You'll on and talk to us. Yeah.

All right. Alright. Thank you guys.

It was, it was great. Thank You. Slo Analyst Ventures, Mitchell.

Thank you. Crazy when you think about it, huh? I, oh boy.

I just thinking about all the investment conversations we've had with VCs over the years and how much, this is such a huge factor in our market, and, you know, it was a boutique thing in Boulder, Colorado when we did still, still secure. Yeah, it was, well, Yel was a boutique thing back in 2007. Yeah, it was.

I, I remember. I remember. Anyway, hey, I hope you've enjoyed this very, this episode of Still Cyber Mitch, and I'll be back in about a week or so with more guests, more cyber news.

Hey, RS a's coming in a couple months. So we'll be ramping up for that. But until then, this is Alan Shimmel And met Ashley, And you just listen to Still Cyber.

We're back here with some more, uh, coverage from our AWS reinvent recent, uh, video stand. Uh, if you haven't seen some of our other AWS reinvent, uh, coverage, you know what, at this point, most of the videos are up. You can catch 'em on text, drunk tv, on the text, drunk tv, YouTube channel, or on our Text Drunk TV OTT app.

If you've got Amazon Fire or Roku or Apple tv, or even iOS or Google Play, I, you can get the O TT app there. Um, but let me introduce you to our guest here. His name is Robert Cilla Cer Cilla.

Yes. Close. Rob, I was close.

I left the S out. Robert Cilla, first of all, Robert, welcome to Text on tv. Thanks you for having, it's the first time he's been on, so glad to have him on.

Robert, you are with er as, unless you just took the shirt. It is a great shirt. Possible shirt.

It is a great shirt, but I am with sus. Okay. And tell us what, what's your role at suse?

So, I am the Director of Technical and Community Marketing. So I handle our community efforts around, mostly around our consumer community. And we, because we have multiple communities, um, it's like that with any tech company.

So direct to consumer kind of stuff versus, Uh, no, when I say consumer, it's people who consume our technology Okay. Is the primary focus. And then our secondary focus is people who contribute.

And on the open side, their focus is slightly different. Where they focus on contributions and less on people adopting, you know, it, they, you know, they kind of build it, it they will come over on that side. So they cater to making sure the project package maintainers are taken care of.

Um, and the needs of these two communities, don't, they overlap, but they're not the exact same. I love it. You know, we've, over the course of AWS reinvent, I bet you I interviewed a half a dozen to 10 SUSE people.

Mm-hmm. Not one of them really spoke about the, they mentioned the community, but they never really spoke about the community. And so let's start right there if we can.

When we talk about the SUSE community, and you mentioned there are different facets, aspects of the community, but how do you define this community? Can you give us sizes? Give us, you know, I don't even know how you would define it.

We, I, I define our community as a large group of practitioners who enjoy the technology, and that is the binding glue that brings them together in our community. Um, to count it, it's hard, um, because you people are in certain channels and they're not in others. And we estimate anywhere between, you know, 45 to 65,000 people, um, who are active, who, um, they participate in Rancher Academy, which is a LMS platform.

We put out, we want people to learn about our projects that, that are out there, or they're in our Slack channel, or they're engaging with us on social media and we understand there's crossover. So that's why it's an estimation 'cause Right. I don't, we don't track exactly who's who.

That's just kind of creepy. We just want you to show up for its Well, But that's, that's part of that open source mantra, right? We, we don't track.

Yeah. You know, we're not looking for your blood type or DNA samples like that. We don't wanna know what Your kids' names are.

We don't That Or even your birthday. Yeah. But, um, so a lot of it is online, it sounds like.

But then like in an event, AWS reinvent, are there any kinda suse community activities tied to it? We Do a few videos that we post out the community, um, does crossover with AWS slightly, um, when it comes to some of the projects, AWS does have a, a large user community, and there's, there's some crossovers there with that. And we see it more so on the consumer side, very little on the con contribution.

Um, for us here, it's just, you know, showing what's the latest and greatest on AWS because we understand that commu there are community users who, you know, they're not customers, but they use our, our projects in AWS and we wanna make sure that we, I don't wanna say meet their needs, but know we acknowledge that that's where they're at. And, you know, That's portal they, and they matter. They, they matter.

I get that. What about in-person events in the community? Not just at AWS reinvent, but, So when we have any large event that, that we try to attend, that piggybacks whether what our comm, where our C's at, whether it's here at Reinvent or Coop Con or Open Source Summit, we like to engage with our community, let 'em know that we're there.

Um, we always have community team members on staff at these events to ensure that, you know, like they can meet the people that they talk to online. Like these, these are kind, I don't wanna say they're, they're rock stars in my mind because they're, they're great individuals on our community team, but I, I wanna make sure that they can connect, you know, in person just 'cause, you know, it's post COVID world, you know, having that interpersonal connection is, is nice sometimes. Sure.

Absolutely. Let me, um, I, I, I, one of the companies I had started was called the DevOps Institute. We sold it about three, four years ago.

Mm-hmm. But we had a, a nice community. It was very simple.

It was very easy. Well, it wasn't that easy, but one, one part of the community, the people who actually had taken our certification classes and our courses mm-hmm. And those, we did know their children's name and their date of birth and all that.

'cause we knew who they were. They had a, you know, they took classes and they were certified. The bigger part of the community though, were just people who maybe, you know, didn't take a, a real certification class, but somehow consumed our content or, or what have you.

And it was always the discussion we always had at the exact level is why would those people want to be in our community? What would, like, what, what's the advantage of being in a community, if you will? Uh, Well, I, I'd like to, I will speak, I mean, in any community, but I wanna speak towards the, the technical community.

'cause you know, it's what we're talking about, and it's fairly relevant, is that individuals have to take some of these skills to work. And they don't want to know that. They don't want people to know.

They don't know. So being anonymous, being able to go and adopt, learn and grow outside of your normal work environment, to come back in and say, I, I, I don't, I know this so I can talk to it. I'm, I'm participating in it.

And I think that's where you see it. And it does cross over to non, I'm a, I'm an avid cook. I love cooking.

I love cutlery. I'm in, you know, a community about, you know, cooking and so, you know, new knife skills or something like that. 'cause I want to learn and grow and not think, my wife thinks I don't know what I'm doing in the kitchen.

But that's just the same thing. It's the same adoption that you want to have. And it's not judgmental.

Someone comes to the community, they don't know. It's like, can we point 'em in the right direction? People love to come in and answer questions for them, and they take that back to work, or they take 'em back to school.

Absolutely. So there is the, the, the help you grow. And especially from a work related point of view.

There, there, look, there are plenty of people who are hobbyists when it, especially things like open source and Linux Yep. And, and so forth. Um, but it is, it, it, it's a way to advance your personal career path.

Let's, let's call it that way. I, I, you know, what else I, and this is me talking now. I don't have anything to back it up.

Sure. But I think it's part of human nature to, to want to feel part of something, part of a community. And, and as you said, it could be cuddly, it could be cooking, it could be anything.

But you always wanna feel like, I'm not the only one who feels this way, who has this problem, who, you know, is working on things, solutions to a particular issue. I, I think there's, there's something intrinsic to humanity that wants us, that, you know, drives us to be part of community. Yeah.

It's a, it's a sense of belonging. Yeah. So when you, you, you talk to people like we have our regulars in the community, and you talk to 'em, and sometimes they will just wanna say hi.

Yeah. And, you know, and or they will bring you something that they did. And they want, they wanna show it off.

And I love that because you're seeing someone who has the same type of passion. And it, it makes me feel better. 'cause it's not me going, like, I'm just a nerd here.

There's, there's other nerds like me out there. Love it. So, look, I built my whole business here on those nerds.

Right? I mean, they're, they're the people who watch our stuff and, and consume this. But it, it's, it's part of being in a tribe.

Yeah. Right? It's tribal at, at it's very nitty gritty.

It's tribal. Right. These are people who are in my tribe.

It, it, it may not be a tribe that I live with or, or something like that, but we share that common bond, that common interest and, and they become part of your tribe. And It goes down, it goes even down further where it's like, I, I only like Linux. I don't like Cloud Native.

Yeah. And, and that's okay. And we Have a lot of people who are like that.

And that's, and it kinda, and, you know, there's always rivalries in any type of community, so, you know, we're better than you kind of thing. Mm-hmm. And it's, I it's akin to sports fans.

Right. And then as a Cleveland Browns fan, you know, I don't really fully understand what it's like from a sports perspective, but I'm sure like Eagles fans or someone else out there, you know, with, you know, a better team behind them would understand that level of, you know, rivalry that you have with the technology. Yeah.

My sympathies to you, by the way. Thank you. Okay.

Looks like you're gonna have a good pick at a quarterback. Again, though, this I'm, let's not get into football. Let's, I'm a Steelers fan.

I'm my own trouble. But, um, and I, I actually, my, when my brother who's is, he's one of a fire toing guys, and I say, Hey, be careful what you wish for. 'cause look at the Cleveland Browns, right?

Mm-hmm. But it's all relative. But it is, we are, we're tribes.

It, football fans are definitely community and tribal. We, we still love, it's in that crossovers. We, we each love our teams, the Steelers and Browns.

We would, we would love our teams, and we have those rivalries and we can say, oh, we do this better. And you have, we even have it in the Linux communities where, you know, they don't, there's, there's certain schisms that you have, and sometimes they get toxic because, you know, we're in an online community. Right?

Yeah. And when you don't have the interpersonal things go get, they get dark, but they usually recover the, and that's what the beauty of a community, it, it, like naturally recovers. I I think part of that though is, is, and, and you hit on something when you have a virtual community.

Mm-hmm. You know, it's easy for people to sit behind a computer and say something that they would never say in person. Yep.

And it's easy to misinterpret what someone else wrote and may not, they may not be the greatest written communicator, and they, maybe you're taking it the wrong way, or they just wrote it the wrong way. And, and this, look, I've been in online communities for a long time, maybe 40 years. And, um, well You also, for you, you didn't mention, but you know, we're international.

Right? Right. And you Right.

You guys Are, and there's, and so there's, there's language things. There's language. I went barriers, but you know this.

No, no. But there's, there's miscommunication All the time. And sometimes I come into Slack and I'm like, what's going on?

Why is there a dumpster fire today? And I'm like, oh, guys, he missed, he meant this. Right?

Like, that's not that word that you think It is, but it doesn't take Long. Nope. It does Not.

There's people over the edge, Robert, let me, we're running lower on time. But for people out here who say, you know what? I've been a SUSE fan.

I, or I've been a Rancher fan. Mm-hmm. Both or, or what have you.

I'd like to be more involved in the community. Sure. What's the best on-ramp farm?

io. You can go sign up and you, you get dumped into our general chat and people, and we see, we see people who get put in there and just say hi. And someone from the community team or someone from the community will do, and explore what they have going on in there.

There's a, there's a lively chat. Um, there's random stuff that people, you know, post, there's technical checks. So, you know, if they wanna learn more about K three s or rancher specifically, um, those, that's generally the, the best way.

And, you know, I'm, I'm in that slack more than our work Slack. So really, that's my world. Well, that is, that is, that's your work.

That's my world. So, uh, I come, I go back to work. It's your tribe.

I go, it's yes. And I go back to the work one when I have to, but that's where I, I you'll catch me. Um, is that, that's probably the best way.

And again, this is for the consumer side. When you're getting started in the community, uh, you don't have to come and contribute right away. I always tell people that just come and say hi, and, you know, find where you want to connect.

You know, and it doesn't have to be contributions right away. It doesn't have to be consuming right away. It's just showing up and just being, just taking part.

Excellent. Is this your last show of the year? This is my last show.

Um, I'm getting very busy with a, and I'm gonna do a shameless plug on Scon coming up April 20th to 23rd in Prague. Chea. That's what's consuming most of my time now, is the planning for that on the CFP committee.

So I'm going through being a group of individuals. Atsa are going through a ton of talks with a lot of great topics. So if anyone is in Europe can make it.

I do. Well, I hope to see you there. I'm hoping to be there as well.

Okay. I'm thinking maybe I should submit something. Has anyone submitted anything on AI yet?

Oh, I'm kidding. That one right there is, uh, I think, I think that's the, the vast majority. And I think when I saw, I saw one that wasn't AI related, I was excited.

I was like, Wow, I, I get that way too. It was brave enough to put that one In, put something in, not with It's crazy time to be alive. I know.

It is. Everything's ai. But yes, if anyone can make it, I would love to see you there.

com, find out more information about that. I Love it. Rob, thanks for coming on.

Thanks having me. Thanks. Talking with us today, man.

This is great. Hey, go check out the rest of our AWS reinvent videos. Scon is coming, I believe it's April 20 to 23rd, as Rob mentioned, in Prague, which is a great city.

You don't have to be in Europe to go to that, though. They do have planes that come from here to there. Yep.

And, and, uh, it might be worth your while. It's, uh, I've done Suko, actually, the last Susko I did was in Orlando near our house. Yep.

But it was a great event as well. So highly, highly recommend it. But that's it for here.

I hope you've enjoyed our AWS Reinvent coverage. This is Alan Shimmel for Text on tv. Hey everyone.

Welcome back here to our continuing coverage of AWS Reinvent. You know, we don't do every video interview live at Reinvent because there's embargoes, there's other considerations. And so this is one of the videos we recorded at, uh, reinvent in Las Vegas.

And we're bringing to you now, just a few days later, I want to introduce you to my friend. Do Laur. Dore is, uh, the CEO, I think founder of cid.

Yeah, yeah. Co-founder, Co-founder of, of cdb. I got help.

We all need help. Do's been on with me on Text Drunk TV for years and years, but it, it's not often I get to see him. He's of course, in Israel.

Uh, we were supposed to be in Israel right now, but we're not, uh, for Cyber Week. And it just didn't come together enough. But Dordt, it's great to see you here in person.

It's great to have you. Thanks. Thanks for hosting me.

It's A pleasure. So, let, let's start with this, though. Not everyone has seen you on Tech Drug tv.

We, you know, we're not, let's face it, we're not CNN or any of those, but Yes. Give people a little bit of your journey to, to founding, uh, Sila. Sure.

Um, so I'm a technical founder. Uh, I have a roots in computer science. And, uh, initially in my career, I went to work for a terabit router company.

That early days tried to take over Cisco's core business in, in, in 2000, uh, the bubble burst. So we didn't work that much, but we did have a fabulous product and a drop in replacement for Cisco CLI, I'll, I'll come later on with more of the importance of, uh, drop in replacements in products. Mm-hmm.

Um, and later on I did something with Blade Centers, and then I joined the company, a startup company where I met my existing co-founder, uh, ti and my, uh, existing, uh, chairman who was, uh, the CEO back then. Uh, that setup had had to pivot three times. This is where, uh, I learned how to pivot Uhhuh.

The last pivot, we, uh, came up with the K VM hypervisor. So to, uh, renovate around the new hypervisor, a new approach that, that was the KVM. It worked really well.

And Red Hat acquired the company. We, uh, spent their four years, uh, improving KVM and also the Linux Colonel, and I'm a big fan of it. And, uh, afterwards, we wanted always to have our own startup.

So we, we left Red out and opened this company. Uh, originally, uh, it wasn't around databases because we had a lots of, uh, virtualization experience. So we mm-hmm.

We started with, uh, an operating system that should have bit beaten Linux in, in virtualized workloads. The OS exists still today. And I met a customer yesterday who runs Sila and knows us because of that s 'cause of that os Really?

Yeah. If you don't mind, what os was this? It's called, uh, OSV.

It's, it's a kernel. Oh, Okay. Sure.

Um, They had their moment in the sun. Yeah. Uh, the, the Docker kind of sucked all of the air from the room when we around when we launched.

But, uh, this is where we, we were familiar with other databases. We, we want to show, uh, the gains when other databases run on top of r os to be faster than Linux. And we managed to accelerate Redis by 70% because we loaded the application into the kernel space was faster.

When we did the same with Cassandra, the performance didn't change much. We realized that the overhead of Cassandra, uh, is itself and, and not, and if we replace it with a fast RS it, it doesn't change it. Uh, so we said, oh, that's can be a good idea for a pivot, because we didn't get enough traction.

And with why we rewrite Cassandra from scratch, keeping the compatibility like the Cisco days, uh, also like the KVM days, it's, it's also about compatibility, uh, with, with other things. Um, and we re rewrote Cassandra from scratch. That's what cila DB does.

Uh, it's also, uh, nowadays compatible with Dynamo Beats a drop in replacement, and it's a standalone database that can run the biggest, most scalable workloads in the world. I love it. What a great story.

Huh. And it's also, uh, you know, for, for geeks, right? You, you're, you're a geek person.

I'm a geek person. A lot of the people out here are, we do this. I mean, it's nice to be able to make a living doing it, but we'd also do it because we love Yeah.

Ly playing with this stuff. And, and this is a great story where your passion led you to, to doing this. Um, it's been Now how long would, it's kind of six years, seven years, eight years.

How long? Mm. Uh, now it's, uh, it's more than 10 years.

About 10, yeah. Even, uh, our 11th year. Really.

That's, you know, what, and that's something also, quite frankly, to be proud of, right? Mm-hmm. Because what do they say the average company, if you make it past three years mm-hmm.

It's a big accomplishment. So it, it's, it's all obviously here. Um, now talk to me a little bit about how people engage with cer, right?

There's open source parts of it, there's commercial parts of it for people out there saying, you know, we're always looking for better performance, better bang for the buck. What, how, how do they kind of jump into silla? Um, so, uh, we, we started, we were big open source fans.

Uh, we, we started with open source, actually, uh, a year ago. We changed the license, I remember to source available mm-hmm. At the time, a year ago.

I, I was just sitting here. Um, so it's source available. We, we do have projects which are, uh, open source, like our, What even source available.

Let me ask you a question. In the year you did that, how many people have asked for the source? Um, so PE people do appreciate, uh, the, that It's available, The source, but It, it, this is, but this is something, look, I've been an open source too for 25 years.

The fact of the matter is, 99% of the people never look at the source code or make a change to it. Not, maybe not. 99, 90 8% of the people never look at the source code, never make a change.

You know? And, and so what they really want is free, Uh, yeah. People like free.

And, and we, we have, uh, a freemium offering right now. We're, uh, now it's source available. It's allows us to, uh, allow people to look at the source and, and also have the, uh, comfortability that the source is available for virus cases, uh, for future con continuity.

Uh, but, and we have some control to say, okay, up to this, uh, level, it's free and beyond that level, you need to pay because we are here 11 years on the road. And, and it's a business, right? Someone's gotta keep the lights on it.

I, I agree with you, But I, I, I do understand people, uh, who are passionate about, uh, the source code. And, and there's a lots of, uh, small things and small changes where things matter. And we have, uh, open source, like, like our core engine, it's called csar.

Uh, it is open source and it's license, it is not a GPL, uh, it's license is, uh, uh, Apache because it's important for, for people to use it within their products. And that's why we haven't selected there. There's a a ton of No, Absolutely.

Changes. Look, I, you know, one of the nice things that I've seen happen in the open source community over the, as I said, 20, 25 years I'm involved, is that most users recognize that though, open source may be free, someone's working on this. Mm-hmm.

Someone's entitled to get paid for their time and their effort and everything else. They may, they may quibble with how much mm-hmm. But you, you know, it, it's ludicrous to think that people are gonna volunteer this outta the pure love and, and not make a living, you know, not be compensated for it.

So I think that's been a positive development overall in the open source space. Mm-hmm. Right.

It used to be, oh, you know, you're looking, you're in it for the money. Everyone's in it for the money. We have to keep the lights on.

We've gotta feed our families. But, you know, it's just, it's a fact of life. I mean, and if you don't wanna recognize that because you're some sort of, you know, like open source zealot.

Mm-hmm. Free is in freedom and free is in beer. Don't use the product.

What can I tell you? And, uh, having, uh, paying users allow us to invest back in the product. Absolutely.

It makes the product better, Product better. And so that's primarily what we do. And It's a flywheel Is a, is a vendor that, uh, used to, uh, eh, release both open source releases and also, uh, gated product releases.

You double the amount of releases. I Was just gonna say, what a pain in the Yeah. You know what that is A hundred percent.

I, I agree with you. So there, but there is a freemium version. You can go check it out, play with it.

If you do wanna look at source code, and that's your thing, it's available to you as well. Um, Dora, let's talk reinvent here. You guys are here.

It's been an interesting kinda reinvent. You know, we, when I, I just finished writing an article when I first got here Monday, and I looked at the keynote, you know, agendas and everything. They gave us a press preview.

It was obvious. It was all agent AI all the time, right? It was all about ai.

But over the course of two, three days that I spoke to people and saw things and walked around, see a lot of news about DevOps, cloud native platform engineering, databases, hardware, well hardware's, AI stuff too, but hardware, um, you know, it, I maybe didn't hear as much as we normally hear about, like things like S3 or serverless or Lambda or these kinds of things. But the geeks are still here. The developers are still here.

The ops, the DevOps folks are still here in force. What have you seen? Um, so AWS is, uh, a giant, yeah.

Even more, more than that. Um, and nowadays they do innovation across, uh, across the year, not just them, also their competition. They, they have to, and so there are announcement, I think that they're not holding the announcement just for, uh, this event, uh, recently they released, uh, new Graviton instances.

Yeah. Graviton five is coming. Yeah.

And, and then, and the, and the GRA Graviton four was released. Right. And, uh, we are, we measured graviton four with C db and, uh, it, it offer fantastic, uh, performance.

And that translates to a better TCO. So for us, it, it's super, that's exactly what we need. Um, so there, there's a lot of, uh, gradual improvement always on all of these products.

Yeah. Um, so it's for, for, uh, for, for, I'm, I'm pleased for that. It's, it's good enough for us.

What about, now I know you're exhibiting, what about like, you know, traffic at the booth, conversations with people? What are you hearing? Uh, well, there, there's, uh, no shortage of, uh, of traffic at the booth or traffic, uh, here in Vegas.

Uh, regarding, um, the entire AWS and, and the ecosystem, uh, it, it's mostly about, about ai. Like, uh, yeah. Uh, we, we see that a surge in AI use cases.

Now about half of the use cases are directly related to AI Ins, Cilla ins. Cilla. Yeah.

So explain that to me. What, what's the use case there? Um, we can split it to, uh, three categories.

One category is, uh, that we're part of the AI stack. And, and during the, uh, training and also the, uh, serving processes, uh, the, the stack need to just access a tone of objects and, uh, need the fast database for it. It's part of the AI stack without doing anything, uh, special for it.

Like, uh, uh, distributed databases is in demand for high workloads. And, and tho those are high, very high workloads. Sure.

Uh, and, and can be, uh, part of the big LLM uh, companies, or can be a smaller, much smaller company that started, start their AR journey. That's number one. Uh, number two is a feature store.

Uh, feature store is more of, uh, machine learning, but it's, it's part of AI still. And, uh, feature store allows people to classify a users or, or sometimes agents, uh, automatically. So it can provide recommendations for, uh, e-commerce, for, uh, fraud cases in a variety of other cases.

And we're, we're big in, uh, feature store case and, and feature store needs. Uh, a fast database too, to quickly come up with, uh, to, uh, classification that, uh, you as a user was selected and, and what's appropriate for you as a user either to watch on TV or to get an ad, et cetera. Uh, love it.

This is the second one. And the third one is, uh, a vector search, um, to, to do LLM on your private data set Set. Uh, that's why, uh, the, the, this whole category of, uh, a rag Right.

Was rag with vectored database. Exactly. So, uh, we added, uh, a vector search, uh, eh, ourselves.

And we already have a, a beta that receives lots of interest. And, uh, we, we are going to this month in December, uh, go live with the general availability of our, uh, rag, uh, vector search store. Really?

Yeah. That's fta. So in essence, they could use Stiller as their vector database then.

Mm-hmm. They're creating small language models or, or Yeah. The rag stuff that's gotta be big.

No, Yeah. That's, uh, fantastic. Our, uh, eh, vector search is the most scalable.

We can easily run a model with a billion, uh, objects. Uh, very few, uh, vendors can even get to a billion. And we can do that with hundreds of thousands of requests per second.

So we, we scale, uh, to, to very high numbers. And if, uh, people have a lower medium demand too, like, uh, most will have a model of, uh, 10 million or a hundred million objects, then we can give, uh, the best latency and, and also very low price point. That's fantastic.

Look, there's a lot of people saying that we've scraped all there is to scrape for these LLMs and that, you know, get, making generative AI or even agent AI better by increasing the LLM and the data we have to train is, is diminishing returns. And that the way to go is maybe s SLMs more rag, you know, uh, well, there's some people who say, we need to go away from LLMs all together and go to this world model and stuff like that. Mm-hmm.

Um, but certainly, I, I believe there's gonna be a lot of activity in, in the SLM rag kind of space. And, and not only that, because as we develop AI for specific use cases, I don't need the whole world of the internet. I just need, especially if it's my own proprietary information.

Right. And I don't want to put that out up there. I want it right here.

Just, and so I, I think that's a huge business for you guys. Yeah. Congratulations.

Thanks. Uh, it's, it's, uh, the, the market demand. Yeah.

Yeah. It's, Oh, well, no, That is, it's not just an opportunity. It's also a defensive move.

Because if we won't do it, then uh, customers will go elsewhere. Uh, to, to be frank. And yeah, the, the fact that, uh, people would expect, uh, all of the ease of use of LLM on the public dataset on the internet, they expect to have the same when they come to every vendor.

And to ask it free text search, uh, your questions in, in one liner, and get immediately the best results without diving into a very complicated ui, that's a power of LLM. And sometimes it won't be people, but it'll be agents it, right. Uh, that come and, and automate and, and get the queries automated.

So that begs the question, is there a an MCP server in your future, Uh, in the future? Absolutely. Yes.

All right. Hey, let's fast forward past AWS for a second. People are watching this after the, after the show.

Anyway. You guys have some new announcements that you're previewing here. Mm-hmm.

Share, if you don't mind a little bit. Thank you, uh, for the opportunity. So, um, uh, we'll also move, uh, from beta to general availability.

Our X Cloud, uh, uh, manage platform. Uh, X Cloud is, is, uh, the new generation of our core database with, uh, database as a service management consumption. Uh, the unique thing about it is, uh, our new core architecture, which is called tablets.

It's way, way more elastic than any other database or even infrastructure in the industry. Uh, we, we were okay with regard to, uh, the speed of, uh, increasing the cluster, scaling out, and then scaling in. We were, before this technology were, we were okay, like, like, uh, an average vendor, but there was a demand to do it much faster.

And frankly, we also compete with DynamoDB. We're a drop in replacement, and DynamoDB, uh, was the first NoSQL database. And, uh, up to this change was the, the best in the industry.

You can easily scale up and down, uh, very easily. And, and if your workload changes throughout the day, uh, then, then you can, uh, instead of paying for the peak consumption all the time, you can just have the workload follow, uh, uh, the work, the workload should follow the usage, right? Dynamically.

So that's exactly what, uh, X cloud is. Uh, we, we have, uh, the technology based on components called tablets. We break the gigantic database of, uh, a petabyte of data to five gigabytes chunks.

Right. And we can move them around super quickly. Uh, we, we can also even, uh, it's allows us, uh, both to scale super fast, we can increase capacity, quadruple it in 10 minutes.

Mm-hmm. So you can go from a 500 K to 2 million operation per second in 10 minutes, But could you go back to 500 K in 10 more? And that's right.

So, because Sometimes with these things, it's like blowing up a balloon. Mm-hmm. You know what I mean?

It never goes back to the size it was before you blew it up. So we, we can, it, it's not, it, it's, it's, uh, indeed complicated. Yeah.

But, but we can also go back and, and shrink and, and that's the user workload that, uh, goes, comes and goes, whether it's a Black Friday or, or on a daily manner. Uh, so, so that, that's a big improvement. Uh, and, and big TCO improvements and, and usability improvement.

Sure. Uh, also, it's, it's, it's pretty unique. Uh, we have a short per quart, uh, engine.

So let's say if you have, uh, a machine with 32 cores, we will have 32 independent threads in the server. Wow. Uh, if you have a 64 machine, then we, we will have 64 threads, uh, in, in engines within that machine, and it'll perform twice as good.

32. Now, let's say if you have a 64 way machine, uh, but actually you need, uh, um, 66, uh, threads and you have 64, would you buy another machine for 64? It's, it's expensive, right?

So instead we, we can mix and match, and we can have 1 64 machine together with, uh, a tiny two VCP machine next to each other because of the flexibility and the hard we Distribution And the starting, we, we can combine the two. Haven't seen any other vendor can do that. No.

And what the user receive is efficiency. Uh, they have exactly what they need. They don't need to buy excessive large servers, which are expensive on AWS, uh, They're expensive everywhere.

It's not just AWS but really what we're talking about here is almost like a finops play, right. Because that's, I think that's where we are, especially in cloud usage, right? Look, we're talking about spending $5 trillion on data center AI factories, but the fact of the matter is, when I talk to people, they say, I wanna get control of my cloud bill.

Hmm. I wanna redu, I wanna be more efficient in my use of these resources. And, and that's why I made the joke with the balloon blowing.

That's pretty much how the cloud is, right? It never seems to go back down. People, they want that ability to have insight to turn that dial, and they want the ability to say, how can they do this more efficiently?

Mm-hmm. Yep. And our customer success team works with customers.

And if we both see, let's say you sometimes utilization people can check their database, how much it, it's loaded on an average basis. Most databases are, are not that loaded. Uh, on, on a, when I'm not talking about the spike, I'm talking about normal, uh, day usage, usage overnight, it can be 10%, uh, or 20% utilized, and you pay for the entire thing.

But That was always the pri that was the promise of the cloud. That elasticity was an up and down thing. Yeah.

It wound up being more of an up thing all the time. But it's good to know that's there. So this available, well, by the time people are reading this, it'll, excuse me.

By the time people see this, it'll be available. It, it's, uh, today, uh, a avail dated to, uh, a WS conference available as beta and, uh, the time people see it available as general availability. Excellent.

Good stuff. What else from seller? Um, so it, it's mostly this.

We, we do have, uh, lots of, uh, things that we develop like tiered storage mm-hmm. Uh, in, in other technology to, uh, reduce the bill. Uh, normally we use NVME for fast storage, fast performance, and it's also relatively cheap co compared to different alternatives of, uh, of storage.

But, uh, SS three is cheaper. The problem with S3 is that latency is prohibitive, heavy, big, it's a 50 millisecond, 100 milliseconds. Uh, and with third storage, uh, we can keep the hot data on fast and VME and automatically move the cold data to S3 and come, come up with, uh, a good solution.

'cause sometimes you keep, let's say 30 days of, uh, of history on, on, on Sila in the NVME, but you'd like to keep one year of data and, and access it through the same API and not develop a new access for it. So this allows users to, uh, have one API and, uh, a very cost effective solution. I love it.

Good stuff. You know what, we didn't, we didn't even mention the website, URL for people. Want to go find all this out on their own.

Dig in a little deeper. What's the, what's the best URL to go to dor? Thanks.

com. com. Just as it says underneath is in as lower third.

All righty, Dora, it was a pleasure seeing you. Safe travels back home. We are wrapping up now again, you, you're seeing this after we were here at, uh, AWS reinvent, but it's part of our AWS reinvent coverage.

And if you need to find this back on, it'll be listed under the event coverage. But for now, this is Alan Shimel for Text on tv. Thanks for joining.

It's always been a challenge for business people to extract insights from business data, but AI is changing this. Companies like Lytic are making analytics and business intelligence more visible and friendly to people who aren't ready to write database queries or build dashboards. A great dashboard provides continuing value that makes people want to revisit it, and the best are proactive.

Can AI help companies derive real value from their data? That's the topic on this week's episode of utilizing ai. Welcome to utilizing ai, the podcast focused on practical applications of artificial intelligence from the Futurum group.

Each episode brings together diverse perspectives to explore news and use cases in the ways in which AI is transforming enterprise IT and the industries it serves. I'm your host, Stephen Foskett, president of the Tech Field, a business unit here at the Futurum Group. Before we dive into today's discussion, let's meet who's on the panel today.

Brad. Hi everyone. I'm Brad Shiman.

I'm the VP and practice lead at futurum for data intelligence, analytics, and infrastructure. And of the three analytics is my favorite. So I'm, I'm quite happy that we're having this discussion today.

And Paul, I'm Paul Blankly. I'm the CTO and one of the founders of Alytics Alytics. It is an analytics agent that helps answer questions, uh, that people will need to ask in their day to day to make better decisions in their work.

This could be anything from an executive making a decision about, uh, how to better allocate resources, a marketing person allocating ad spend or procurement, making better decisions on, on how they, uh, buy product for a manufacturing company. And as I mentioned, I'm Steven Foskett. I've been hosting the utilizing tech, uh, podcast and utilizing AI podcasts, uh, for, uh, five years now.

And we've watched as AI has grown in usefulness and practical applications, uh, we launched the utilizing AI series with the futurum Group analysts last year and all the time, the plan was that we would eventually be inviting on guests to join us in the conversation who are doing interesting and relevant things with ai. I got an a briefing with Lytic right about the time that we were planning this series. And I have to say, it really, um, appealed to me because both of us had the same idea, which is basically, AI is cool, but it's also useful.

So let's talk about how it can be used for practical business use cases, and that's really what Lytic is doing. So before we begin, Paul, let's kind of dive in. What was the question that was being asked that you decided to apply AI to answer?

I think some of the best ones are, are questions that you can't easily answer by yourself. So a good one that of where I used our own product, uh, to analyze our own users of our product was I had this theory that people were using the product in different ways. Most of the people chat with the product, but I, I went in and I asked Zoe, our, our agent, that same question.

I was like, Hey, can you break out how people use the product based on their usage of different features into different clusters? And then, you know, gimme a sample from each so that I can go have some 15 minute conversations with them and better understand their use cases, what they're trying to solve. So Zoey went in and helped me, you know, find basically three buckets of people.

There's like the people who use, uh, chat the most. They're talking with the AI agent, definitely the pro, like the bulk of our, of our users. Then there's people who use that and then also use dashboards and other sort of more traditional reporting mechanisms a lot that also makes sense.

Then we had a few people down there who kind of just use the dashboards and like also never the thoughts to the AI agent. So I was able to find these three clusters and then go and have conversations with each of those to better understand their use cases, where we're meeting their needs and what we could do better as a, as a product. So that's an example from my just day to day of how I use, uh, how I use agents to, to better help my analytics needs.

Sorry, Brad, I was waiting for you to just dive in. Uh, we'll, we'll cut this Bit out. I didn't know.

Yeah, I, I, I apologize. Dive and Corey. Yeah.

Apologies, man. I, I didn't know if you were doing this more formally, Steven. Yeah, No.

Yeah, I might have, but I didn't. Yeah, so you're, I expected you could get my Way, so, okay. Let me just start like, I'm, I'm just responding.

Yeah, I I like very much what you're, you're saying, Paul, and, uh, yeah, I see this in our research, uh, quite frequently that, um, as data professionals work through their DA daily tasks, which are many and varied, um, that they are, have found a great utility in using, uh, ai. I, I think initially, um, in the market, especially after we invented Transformers, there was this, uh, sort of idea or a thought that, well, they can't handle structured data, they can't work with a CSV file, they'll just fall over. Or, you know, we, we can use them, but, um, we can't trust what they say.

And I, I find that ironic for a couple of reasons, because, um, in, in my, I'm also a practitioner as well as an industry analyst, and in my, um, job as a practitioner, I, I find it invaluable for, um, almost daily, I'm, I'm finding new ways to use this, uh, in, in making my job easier. Whether it's like you're talking about doing some basic segmentation or if it's just data cleaning and prep, uh, or if it's something, you know, more deeper like data mining, like, like you're doing, you know, it, it is tremendously, uh, I I would say useful and trustworthy to a degree. But I, I say it's ironic because when I look at the industry and I look at how, you know, companies are using BI in particular and they're looking at dashboards, I feel like they, uh, have more trust, uh, you know, in, in just their gut instinct or in the dashboards themselves.

And they, they put more emphasis on that than they do on, on ai. So we seem to demand more transparency and accuracy from AI than we do for bi. We kind of say, yeah, it's a black box, but I trust it.

What's, what's your, um, experience Paul at, to your, at Lytics in terms of how your customers are looking at their dashboards versus ai? Oh, yeah, I think that's a, that's a really good point about how a lot of times people trust their gut instead of, you know, whatever, whatever's on their dashboards. I think there's, there's a really good reason for that.

Actually, the reason for that is, is maybe best sonified in, um, in, in a conversation I had with one of our, with one of our pilot customers. Uh, so I was talking to this, to this woman who's a, who's a PM on, in a major public company, and we were going through, she was asking some questions. The only, we'd only imported a few data sets so far, and she was like, Hey, well I'm, I'm not really getting that much out of this.

Like, what's, what's going on? And I was like, well, you can ask about all the stuff you could ask about on these, you know, that's on these two dashboards. And she was like, well, I don't want that.

It's already on the dashboards. And the, the dashboards don't tell the full story. That's why if you're a PM trying to make a nuanced decision about how people move through your login flow, knowing some basic high level numbers doesn't really give you the information you need, doesn't really answer the question you care about and then therefore just not that relevant for you.

It's maybe useful to monitor to understand kind of the, the basic parameters of what you're looking at, but it's not gonna actually impact your decision. You need way more sophisticated analysis than you can get out of a, out of a dashboard to actually impact a decision. And that's why for these, these analytics agents, uh, what we're building at lytic to be impactful, they've, they've gotta be able to go way beyond what you can do in dashboards.

The PM has to be able to come in and ask really, really nuanced questions, which are not only the valuable questions for him or her, but they're also the ones that are way harder to explain your methodology. We explain what you're doing. Um, and that's what, that's one of the things that the agent has to really excel at to make sure that, that, that that end business person can trust and can actually act on confidently on the data that they got back.

It does seem like people are, are trusting AI already in many cases, to give them truthful answers, even as there's this sort of understanding that, uh, generative ai, you know, for example, the search box, you know, Google type generative AI isn't always trustworthy. It seems almost a paradox that people trust AI more than they themselves would say that they trust ai. And at the same time, I definitely feel like people trust AI more than they would trust people.

You know? And, and that's a, you know, even people who would know things, right? I mean, and I wonder if, if, um, you know, kind of looking at my history with, uh, data professionals and how they've interacted with the business, um, to Brad's point, it does seem like sometimes data professionals have labored long and hard to come up with a dashboard or to come up with a metric and, and only to have somebody say, well, yeah, no, and, and I wonder is, is, is AI going to change that a little bit?

Are people going to trust AI more than a per more than a data pro? I think they even use dashboards in the future. Sorry.

Sorry Paul. But, uh, yeah. Will we even have dashboards?

Are they, are they necessary? Is, you know, are we moving toward an interface that is the human voice and nothing more? And, uh, you know, will we have what a lot of people in the industry would just call headless bi, that's ag agentic that would, you know, find the answer to your question and do, like, Paul, you're talking about with digging deep into the meaning behind the data and the context for that meaning, and putting that into perspective and bringing back like good answers.

I would love that. Yep. I, I actually think there's two different use cases in data that are, that are often conflated.

And that's why we get the, like, dashboards are gonna die. I don't think dashboards are gonna go anywhere. Um, dashboards solve this monitoring use case, which is like, I need to see the same stuff every week.

For me that's like, Hey, what are our usage in the different model providers? How many people are using Claude now versus OpenAI? How many loggings did we have?

How is that trending? Like, which customers are active, which customers decrease their activities? Like, that's just monitoring stuff I wanna see every week regardless.

Um, but then the, the really valuable use cases usually aren't monitoring. It's usually a question that you're like, oh, okay, I really need to deeply understand how people are using this. I need to understand where this login flow is breaking.

I need to understand, you know, what's going on in this area of the business. And those are those deep questions that are just not served well by dashboards, and that's what the, what the analytics agents are gonna, are gonna take over. Yeah.

Do you think, Paul, that, um, through a analytic agents, um, that we can get around, what, what seems to be, to my, to my mind, one of the biggest problems with, uh, dashboarding and traditional bi, and that is utilization across the business and what that means in terms of, you know, how a business actually runs. We, we've been laboring for decades now, trying to, you know, have data professionals build beautiful dashboards that get used. Uh, but unfortunately, you know, it, it typically ends up where, you know, the analyst spends weeks or longer building a dashboard that nobody uses.

Uh, and there's no true understanding of why it isn't getting utilized. But, uh, I would love to, to think about, you know, uh, as, you know, an industry watcher, the idea as you just talked about, of being able to balance those two, you know, the two sides of that coin, the, I wanna, you just have the same data all the time, and I wanna be able to dig into what I want and to have that available to everybody in the business. You know, is that possible?

Do you, do you think from, you know, nalytics perspective that we can change the business as we've been trying to do for decades now? I think, I think there's, there's two ways to think about that. It's one, I mean that the, the business team just obviously are not getting what they need out of the, these dashboards, even if it takes a very long time to develop, um, or the dashboards answer a onetime question, which I think is probably most of the pattern where a business person has a need.

That need is for a specific one time stone. A dashboard gets built, it takes a long time. By that time, it's almost a rear view mirror.

It comes in, the person looks at it, they, they understand the one thing they need to understand, and then they never revisit it again because it was never a recurring mood. It was never something they needed to monitor in the first place. And dashboard needs to buy a vehicle to, to, to provide that answer.

The, um, the other one though is like, how do you increase utilization? Like, how do you get business people using data more often? There's certainly the, you make it really easy to ask questions.

Anyone can come in and ask an analytics agent a question, get a good answer back. And, and that's a great thing. That's a great utility.

That was, I think, actually only the first step in this because there's only so often you have a question, you think, oh, this is actually something that would be really helpful to have some data to like back up or support my decision here. That that only really crosses your mind, not that often in the workday. So you wouldn't expect a, a massive amount of questions that are just people coming in down, um, to really solve that.

You need to do what the, what the absolute best in, in our industry do, which is you're proactive. You're, you're, you're not just, whenever you're asked a question, you're reactive and you're coming back and giving an answer that's good. Um, you, you need to say, okay, well, if I was a VP over, you know, our, like procurement in a manufacturing organization, what are the things that I would be most concerned about?

How can I proactively go? And before my VP comes to me with questions, I, I come to them and I'm like, Hey, you know, I've, I saw this trend in, you know, these parts suppliers. I know that we have rebates that we can claim on suppliers once we increase exit volume.

I found all those suppliers. Here they are. I've drafted emails even, like, just gimme the, okay.

And I can send those for you. It's like, that's the level of productivity that the absolute best people in organizations have. And I think the agents can absolutely emulate that behavior.

And that's, and that's where you get the utilization that's really impactful. But it's not just people coming in and asking the agent questions. The agent needs to be proactive.

The agent needs to be able to go to them and say, I thought this would be relevant for you, and it needs to be relevant. And that's how you build that kind of, uh, continuing value. And you get people to really invest in a tool, I think, is to have them have it be something that is not just, um, not just there for them, but like you said, kind of providing proactive value.

It is exciting to think that that is possible in this BI space. Because again, you know, like we said, BI has always been a very reactive, you know, uh, kind of plotting process where you basically, you know, you're almost requiring someone to know what they want before you build it for them. And then they, then you go and do it, and then it, you know, they go back and forth and, you know, I mean, Brad, we, we, we experience that sometimes internally with our dashboards.

And it's frustrating because, um, what you really want is something that, that just gives you that information. I think about the metaphor, you know, you look at the vehicle dashboard in your car, right? You know, it's providing you the key information right.

When you need it. That's really what we want from our business analytics, right? Yeah.

You want your car to have a dashboard that, that shows the things that are relevant to you at that moment in time. Like your, your left tire has less traction, uh, coming into this turn. So I'm going to turn on four wheel drive for you so you don't crash.

That. That's what we're talking about here. And we've seen for, you know, quite a few years now, especially after the, uh, chat GPT moment that, um, you know, companies that were building bi tooling we're, we're trying to do that with SQL text to sql, voice to sql, and with, uh, things like explaining dashboards and, uh, tooling that, that could automate or at least augment some of the workflows that data professionals went through so that they could maybe have more reactive and more immediate, timely access to data.

But, you know, I, I feel like we're still a long ways away from that overall, uh, as you know, an industry just because the inertia that companies have, uh, in, in getting to that and that mindset, uh, is something that I, I think is still gonna take some time to shed, even if we have the tech in hand to do that. Paul, do you see in your customers any, any kind of like, um, do, do they seem like they, they understand and grasp how they can make that leap to that, that real time responsive dashboard for their, for their car? I think, I think, I think a lot of people do, but it's not, it's not even really distributed.

It's kinda like the future's here, but it's not even really distributed. Uh, what, what we see happen most, which you'll actually hear this from a lot of other companies that are, that are sort of AI natives like us, is you'll have these power users that just do incredible things. They're usually the people who are, you know, more, they're interested in ai, they wanna push these tools to their, to their limit.

Um, one of these users in, in j Crew, uh, Heon, and he did a deep dive on trying to, we better set up the assortment in our Upper East Side store, some of the most expensive real estate we have in the country. Um, and what he said is, Hey, we've always put stuff, we only put clothes in this store based on historical purchases in this store. What if instead we looked at the humans who are shopping in this store and picked what they buy through all the channels that we know about all the other stores we shop in everything.

And we, we tailored the store for the persona that most often shops there. So we took that approach, which is way more complicated, but with, with Zoey, uh, we could able to do it. And they actually redesigned the Upper East Side store and in, and increased dramatically the amount of children's flows that were there, because that's where they found out that that, that that persona wanted to buy.

And that's the kind of thing that you have this power user that just has outsized intact on the organization, um, because of that. At the same time, you have a lot of other people coming in, getting answers to questions, getting answers to questions like, how many transactions did we have that came in through such and such campaign? And, and those are fine, those aren't bad questions, but those aren't at the same level of impact.

So I think the thing that we'll increasingly see as people get comfortable with AI products and, and these, uh, these power users can kind of influence other people in the organization, is that more people feel comfortable coming in and asking those big questions. Like, try it, try to get it to do something you don't think it can do. Maybe it'll surprise You, right.

Break, break it. Yeah, exactly. And those are the kind of, um, sort of unexpected insights I think that, that companies wish they could get from their data, right?

I mean, that's what, that's what they really want. That's why they've been doing this all this time and trying to build these, you know, data warehouses and building analytics and building dashboards and trying to get business intelligence. I mean, it's right there in the name, uh, but unfortunately, I feel like the whole process has been just so reactive instead of proactive, like you're describing that they just haven't been able to do it.

Is that your experience, Brad? It is. And I, I would say that it, it's, it's funny because, uh, when you talk to data professionals, uh, and across the spectrum, so every, everyone from a casual business user that's using data to the, the person that's in charge of maintaining, you know, realtime data pipelines, um, or, or the data scientists working with the data, um, you know, in, in very select deep ways.

Um, and all of them have, like, you know, said, you know, we are shifting toward the business. We want to be able to focus less on the syntax and more on, you know, the intent. And one of our, one of our, um, uh, we, we do our yearly prognostications, and one of mine this year for this re this area is the rise of the AI Shepherd.

I'm, I'm calling them. And it's, it's basically to say that, you know, we, we've tried augmentation. That's old news, new interfaces, natural language.

Uh, people don't want to write SQL to, to get something done. They want to just state their intent. And how you do that, whether it's in an interactive dashboard that has Zoe, let's say, as your co-pilot to work with you on that, or whether that is just in a chat interface or whether that's in a line of business app, uh, that you have, you know, your traditional pull downs for what you're working on for that workflow is irrelevant.

They, they want to just be that, they want to be the person that has AI with them to, to make these decisions, to bring back these insights. So we're seeing, you know, the traditional data, uh, professionals shifting toward this. I'm not a technician anymore.

I, I'm more of the validator, curator, adjudicator, uh, facilitator to, to, you know, innovation built on top of data. So they want it, they, they really, you know, the data professionals really want it. The business users, I think, you know, need to, to sort of see that.

And as Paul you mentioned, you know, if you have people in the organization that can trumpet that and, and promote that as, yes, this is here today. We can do this today, that that's what we really need for everyone in the indu in the organization to be able to say, you know what? I don't have to wait two weeks for somebody working in SPSS to build a dashboard for me.

I could get, I get an answer like right now. Totally. I think the, I think your, your way of framing it as, as AI shepherds is really good, because when you think about what are the barriers to, to these agents actually working inside of a complicated enterprise, there's like two facets of, there's context.

There's, do I know what you, um, the context part is straightforward, but still complicated, which is there's a lot of historical patterns you have. There's a lot of facet knowledge hidden in dashboards, hidden in databases, hidden in the, just the head of, of the data, people who have been having to answer these questions and accommodate all the weirdness in their data. Uh, because everybody's data is weird to some extent.

And, and getting, getting all of that information and making it really easy for, as you use the product and as you get value to add that context in as you go, instead of having to kind of put it all together and boil the ocean before you can start asking any questions. So, so that's absolutely key. That's like gathering the context.

The other one is the explainability, and well, like, why do I say explainability instead of trust? Because any really good analyst, the really elite analysts are gonna come back and not just explain to you like, Hey, I got this such and such number. They're gonna say, Hey, I follow, this is my methodology.

Like this is, this is what I followed to get to this. And they're gonna actually show their work. And what that does is, instead of the VP or whoever coming back and being like, that number's wrong, obviously, like, um, have you guys even looked at this before?

Um, they're, they're gonna say, oh, okay, I see you followed this methodology when I wanted you to do this, but I didn't actually say that you should do this other approach instead. And that's the same way that an AI agent builds. The, the trust is through that explainability and understanding where that end business person can understand, Hey, this is the approach you took.

Great. That's what I wanted. Or actually, I wanted to see it a different way.

I wanted you to approach this differently. And, and those are the two sort of fundamental things. It's like that context of like, what's going on in the business?

How do I answer questions correctly for this business? And then the showing your work, the, like, how did the end user know what I did and can be confident in the, in the end result? You know, what AI is really good at right now, when you, when you look at, um, areas like, uh, software development in particular is in documenting, um, that methodology, um, and in turning it, we, we've had some tooling now that just has swarms of sub subagents that all will go toward tackling a, a given problem, and they'll come up with a plan called a spec, spec driven development.

And I think that we should start seeing if we're not already the data professionals picking up that same methodology for how they do it, because AI is terrific at building that, that taking that knowledge that usually just sits in somebody's head and operationalizing it. Yeah. You know, that's, that's a really good point.

And I think that that's maybe something that we can kind of step back from the specific conversation about business intelligence and, and, and talking to the folks who are listening to this, who are not maybe in this field, but are wondering, you know, what, what, what could their takeaway be? The idea that AI can help them, um, I guess understand the whole process, you know, talk to us a little bit more about that, Paul. Yeah, I think that's, I think that's maybe the most important aspect because what you, what you want is you want a virtuous loop where the person can ask the question, get an answer, they really understand how the AI went about getting that answer.

Then they're more equipped to ask a better follow-up question. They're more equipped the next time they have a question. They're like, I actually know a bit about how this, this works now.

And then they're, they're able to ask better and better questions as you go. And you get this virtuous cycle where you ask a question, you learn a little bit more about how this is structured, you get the answer you need, then you can ask better questions as you go. And that you get this virtuous cycle where people are asking better questions, getting better answers at a more relevant to them and all because they actually understand what approach the AI has taken.

And that's, uh, that's the just so crucially Important. Yeah, I, I'd love that because, um, as we were just talking about with, with documenting all of that institutional knowledge and not losing out on, on tribal knowledge, um, is one of the biggest challenges that companies face. And if you can introduce a technology, whatever kind of technology that preserves those and, and honors them and puts them to work in improving that cycle of question and answer, uh, whatever domain you're working in, whether it's bi or, you know, sales enablement or, or you know, any particular area in the business that, you know, an investment in that is an investment in the future of the company.

'cause as we all know, um, jobs are changing, roles are changing, the business itself is, is changing. And so we need to, as an industry, invest in the technologies that can, you know, take the concept of this business, everything from the semantic layer up to the, you know, business decisions and the data points that sit on that interactive dashboard. And to make that more resilience and more responsive to, uh, an ever-changing environments that we all live in right now.

That's what we need. Yeah. And the real, the really important part there is, it's gotta be really easy as you go, as you're asking questions, the agent is remembering things.

You are able to say, Hey, great. That's that concept. Remember that now it needs to be really, really easy as you're going.

It can't be like a big, you know, months long project. Like set something up before you start using it. You've gotta dive in and start using it now and have it learn with you as you go.

That's the, that's the pattern. Yeah. It's called Forward slash memory as you're, as you're typing.

And, uh, they could tell it to remember anything you want. Well, you know, it's funny that, um, you know, the most effective, um, you know, AI power users are generative AI chat chat power users that I've talked to. The, the way they do it is kind of flipping it on its head and having the, um, having it interview you instead of you interviewing it.

So instead of saying like, Hey, give me an answer, you say, Hey, um, if I wanted to achieve an answer, what were the, what are the questions that you, you know, I should be asking What are the facts I should be bringing forward? Um, how should I be thinking about this? And it helps you to organize your own thoughts and your own queries in a way that can help then the AI helping you.

And, and I guess Paul, that's, that's the kind of thing you're talking about, right? That, that, that the more questions, the more interaction you have, the better it gets instead of the worse. Yeah.

Yeah. Yeah. It's, it's gotta improve.

And then I think, like you said, the other, the other really component, the, the really important component there is asking the right questions and asking the right questions means, just like you said, you're not asking for a specific data point. You can do that and it'll give you an answer, but you're telling it the problem you wanna solve instead. Yeah.

Because almost inevitably when you do, it'll, it'll pick out that data point you had in mind for that problem. That'll, it might also add another one that is really relevant that you just didn't think about. Humans are bad databases and the language models are actually pretty good databases, so much better than humans.

So ask them the, ask them your goal question, ask them what you're going for, and they'll probably catch something that you just didn't think of in the, in the moment. It's a really helpful pattern. Yeah.

I like to have my agents, um, use the Socratic method to, to argue a point. Well, on that note, um, perhaps then, shall we continue the No, I I, I, I'm not even gonna try, I'm not even gonna play that game. That Was cute.

Yeah. So this, this has been a really interesting conversation and I really appreciate the fact that we were able to, you know, kind of go from specific to general here, and that we're able to come up with some really interesting ideas for how people can make best use of this technology. Um, before we go though, I do wanna give you a chance, uh, Paul, uh, tell us a little bit more about Lytic and, and where people can connect with you and find you and learn more.

Yep. You can find me on LinkedIn. com.

If anything that I've talked about is interesting, please, you know, chat with us, book a demo. Um, I'll also be talking at day-to-day Texas in a couple weeks, so if you're there, gimme a pin. I'd love to, love to chat, uh, while we're out there in Austin together.

Great. Um, Austin, hey, that's where Futurum is. Uh, Brad, how about yourself?

I know you're not in Austin, but, uh, where are you gonna be lately? Uh, I'm, I'm actually home for a couple of weeks, which is, which is nice. Um, and I'll be working on a couple of, um, comparative reports that are themselves using generative AI for, uh, a project that we have internally, uh, here that, uh, we call Signal for Signal Reports.

And one of those that I'll be working on is around semantic bi tooling. Mm-hmm. And, uh, so analytics will be, will be featuring in that as well as many others, um, because this is a rich, rich marketplace with a lot of great people working on, on this solution we've been talk, talking about today.

So I'm, uh, I'm looking forward to, to getting that going. Yeah. And if, uh, people wanna see that report, uh, Brad, where can they find that?

com. Uh, and they can find me on LinkedIn all the time at Brad Shiman. All one word.

Excellent. Well, thanks so much for this, and, uh, thank you everyone for listening. I hope you found some, uh, interesting ideas here for your own use of ai, your own practical utilization of ai.

Thank you for listening to the utilizing AI podcast this week and every week. If you enjoyed the discussion, please do subscribe. Uh, you'll find us on YouTube as well as in your favorite podcast application.

And of course, a rating and review would be helpful. This podcast is brought to you by the analysts and experts from the RUM Group, where insights meet ai. For show notes and more episodes, head over to Text Strong ai, the utilizing AI YouTube channel, or the Text Strong TV app.

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Hey everyone, I hope you like that video. You know, we are, uh, one day out from Predict, I forgot for a second. We're live.

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That's my promo. Welcome to Textron gang. Happy Wednesday.

We're live again. Um, for those of you who've watched Textron Gang before, our gang today is kind of core regulars. We've got our man in the valley, John Swartz, our lady in front of the brick wall, Terry Robinson, and of course, the dean, Mike Ard.

Gang, welcome. Thanks for joining us, Mike. Beyond Predict being the big news, it's, and you know, of course it's ai, everything we talk about seems to be ai.

We've got some news in, in out there. Microsoft, Microsoft's doing their share to stem the affordability crisis. What affordability crisis.

So, you and I talked about this on a previous show, and you were banging the drum about the fact that people shouldn't have to pay for the electricity that is being consumed by all these AI data centers. So I guess the president heard you and had a chat with Microsoft, and Microsoft stood up and said that they will cover those costs in terms of how much electricity that they are consuming. I haven't heard yet from the rest of the builders of those AI data centers if they would do the same thing.

But I sometimes think if I look in some of these small towns, you know, the electric bill for the whole town is a rounding error on some of these AI projects. So what the hell? Why not just pay for everybody's electricity?

But, um, what's your take on this, Alan? I mean, you know, is this a moment in time where the, the president's doing the right thing? What do you saying, Saying?

Can you say that again? The president heard me. I'm flattered.

I'm flattered, but, um, look, the devil's in the details here, guys. What is, what does it really mean that Micros Soft's gonna pay the full cost of AI data centers? And should we be grateful that they're paying their own bills and not shifting it onto us?

This sounds like a typical kind of con game, and we know who the con is, right? I should be let, let, let's think about this. I, let's think about this.

These sobs are building trillion dollars worth of data centers running them to charge us to make their profits. And you want me to be grateful, thankful that they're actually paying the cost for it. Yeah.

What world are we living in, you know? Thank you, sir. May I have another?

Mm-hmm. Thank you, sir. May I have another?

Here's Mike, you're onto something. Here's what we should be saying is, hey, as long as we're building all this infrastructure because of these data centers you're building, it is a god darn rou route of grounding era to, to cover the cost, at least the municipal costs, if not all of our individual costs too. Throw that onto the pie.

What the heck? You're not paying taxes most of you for 20 or 30 years, 'cause you got all kinds of abatements to, to build these data centers. We can't regulate 'em.

'cause regulation can only come at the federal level. Now on ai, it's the least they can do. But devil's in the details.

Here's the real issue. Are we talking about Microsoft just paying the ongoing monthly electricity bill, right? That most of us pay every month?

What about the CapEx expenditure to build this critical infrastructure to generate these things in, in one case with Microsoft, they're taking three mile island at a moth balls. Are they covering the moth ball cost? Well, everyone's grandma will be a little happy to get free morph balls, but you know, what about, what about the, the, the CapEx cost?

Is that include it or is just just the monthly I I don't see that detail in there. Or are they just covering the CapEx and, you know, not not monthly kinda stuff. You know, I, I'll see it when I believe it.

I I'm not, you know, kudos to Microsoft for some good PR here and fighting this imaginary affordability crisis that we seem to be talking a lot about for something that's not real. But, um, let's see what happens. Yeah.

What Is your think here? Is this part of some larger political effort around affordability because, well, we've seen them about capping credit card fees and suddenly all these things that they're doing that have nothing to do, allegedly with an imaginary affordability crisis. Exactly.

So this is all, as you said, I think earlier in the green room, this is all about affordability and playing to the base. So we think about all these, uh, data centers and this infrastructure that's being built. And there are places like Texas, Louisiana, the Rust Belt, uh, and the folks are gonna be paying higher energy costs, evidently ev eventually.

So Trump, in a sense, is playing to his base. So he wants it both ways. He wants these companies to build out, it's a massive scale.

He doesn't want them to pass on any cost to the consumer. And I think another thing that he's also probably taking into consideration, although I'm I'm not sure he quite understands it, is that the, none of these places are gonna create new jobs. So he is trying to, he's trying to probably figure out a way to save face.

And I also wanna point out that Microsoft, to be the first company to agree to this, uh, I don't know, I idea there, in a sense, Microsoft is the master of Mollifying, the, the White House and federal government, you know, after they went through the whole thing with the Department of Justice and Windows back in the day, they have been very, very savvy and, and played the white knight among tech. So I, I suspect you're gonna start feeling pressure and start seeing announcements from other companies like Meta, OpenAI, Oracle, perhaps, who are gonna ae to the same demands that, that Trump has. Um, you know, one other thing I've mention is this kind of reminds me in a weird way of, uh, these sports palaces that are built on the backs of the, of the backs of the, the fans and the, the residents of areas who pay taxes to help facilitate building of these massive facilities, stadiums, arenas.

And it, again, it all goes back, comes back to the economy, and it's all being played into this, as you said, Mike, this political prism in terms of affordability. And, uh, it's all a, a big, a big kind of, uh, power of play to, to show that he cares that Trump cares about the little person. I think all he really cares about is his getting these massive facilities built Well, yeah.

And money in his own pocket somehow. Um, I, I'm just wondering Yeah, yeah. We, we certainly are paying a lot of attention to something that's a hoax, um, this affordability thing, um, as we tend to do these days.

But, um, uh, exactly how does this impact, you know, affordability for anyone, so Microsoft or whoever agrees to, to pick up the energy cost, okay, so it won't add any costs to maybe the average citizen in one of these areas, but how does it reduce anything? It doesn't, unless these companies do, as Mike says, and you know, they pick up the tab for everybody's energy. Well, Alan's point, there's devil is in the details.

So I think a lot of the pricing for energy in various states has been tied to demand versus alleged supply. And whenever a demand goes up, everybody's bill goes up. So it's not really just your bill per se.

And I think, um, they need to kinda look at the way that, and we actually price the consumption of electricity in, in the world because it doesn't align with these data centers. Secondarily, I mean, why not have these guys just build their own grids? I mean, you know, there's, if you're gonna go invest in that level, then might as well go and build a grid and doesn't use the public grid because, well, maybe the public grid wasn't designed for this in the first place.

Well, there you go. Take it from Texas, do your own, right? Mm-hmm.

Grid what Could go wrong. Yeah. What could possibly go wrong, it could go wrong, could possibly go wrong.

Jen, I, I wanna hit on something you said, John, you know, analogizing this to large public works projects that are funded by our tax dollars, such as stadiums and arenas and so forth, coasting the Olympic Games or the NFL draft or something like that. Um, in those cases, there are tangible, measurable revenues thrown off by those venues and those events, right? That Pittsburgh is gonna host the NFL draft this year in, uh, April, I think the 22nd that weekend.

And, you know, they're anticipating it generating hundreds of millions, if not billions of dollars of revenue for the, for the area in ways of, in terms of hotels and food and, and other services. Every stadium right? Creates hundreds of jobs, not just the people working, building the stadium, but the people who work in the stadium, the, the shops around the stadium.

You know, you go down to LA and I, I have, I haven't had a chance to go here yet, but I really want to, I don't know, maybe John, if you have to go down to SoFi Yeah. Stadium in LA I mean, that's like a mixed use project where you have all kinds of retail and, and revenue generating activities going on there every day of the week, 12 months a year. 2 billion project.

2 billion on MetLife stadium with the Giants and Jets play, and how much that generates for the surrounding area, it doesn't add up. Right? And I think ultimately that's going to be the surprise here, right?

All the people, especially in the Rust Belt clamoring for the return to manufacturing and good paying jobs and projects, you know, once the construction's done and the cranes go away and the hard hats get put back in the shelf, what, what's going to be, I mean, there'll be, and, and like I said earlier too, a lot of these projects are getting sweetheart tax abatement deals where they're not gonna pay taxes even for a long, you know, much taxes for a very long time on it. What is the, what is the, besides the noise, what's the plus? Yeah, yeah.

You think about the environmental impact, you think of the lack of jobs, you think of the, the costs, I mean the distinction as you rightly point out, Alan, between the public works and something like these data centers, those stadiums were, I mean the, the taxpayers usually vote on these, these types of, these types of projects here. They really didn't have a choice. And I think in the end results is they're gonna have these massive facilities with minimal humans, probably robots, physical AI operating most of the tasks, and they're gonna be hit with electricity bills that are much higher.

And I think in, in his, in Inable way, Trump waits until the process is already in effect, there's no planning whatsoever. And then somebody taps 'em on the shoulder and says, Hey, you know, our base is gonna get really upset when they get hit with these, these extra costs, and they find out there are no jobs, so we gotta do something, you know, come up with something. And then they, they, they, they strong arm a tech company into saying, oh yeah, we'll, we'll pick up x amount of costs in a kind of vague way to mollify people until they forget.

And then they get hit with the higher prices later. Yeah. Well, and part of the forget is just keep throwing more stuff at 'em every day so that they Yeah.

Distract them. It's the new cycles. Yes.

Right. By the time, by the time this comes through, there's been five other new cycle items. So it's just like, it's shock.

It's crazy. Well, I think also they just don't, people, most people are not, most, a lot of people don't understand, you know, how energy costs are calculated, how, you know, there's, and they don't understand the, the poultry number of jobs that are gonna be offered and they're not going to do their own research to find out too. I mean, that's, I would No problem by the way, are not gonna be in whatever remote location that data center is because we are remotely managing most of those data centers.

So Sure. The people who are working on that will not be paying taxes in that community. And then secondarily though, there is an old joke in it circles one of my favorites, you know, what's the future of the data center?

It's one guy and a dog, and the dog is there to keep him from touching anything. Absolutely. But there's another aspect I wanna just close with.

We could pay more money for a minute for energy, but where is that energy coming from, right? Is it's, you know, Trump media merged with a fusion company. That doesn't mean fusion is gonna be powering these data centers anytime soon.

The fact of the matter is our green ha greenhouse gas emission for the first time in years is now going up instead of down. Yeah. We are already burning more fossil fuels and dirty energy than we were before, and our greenhouse gases are, are reflecting it.

And so, you know, just because we're willing to pay for that energy doesn't mean that that energy doesn't have yet an additional cost. Well, we may not know that. 'cause the EPA is not allowed to talk about health Anymore.

No, Right. Health anymore. The, the quality of our error affecting how many people die.

But make no mistake, unless we get serious about clean, renewable energy, all of these, we can't power these a or, or do something with clean nuclear, you know, the only other alternative is go start burning coal again or something. Well, isn't that on the deck? We Can go to wind power.

I, I know Trump would really like that. Well, yeah, it will kill all those birds anyway. Hey, we, we gotta transit, transit.

I hate using that word transition. It gets people upset, not me. But anyway, we, we've gotta move on to our next segment here.

Um, so a new Taiwan trade deal. I've, I've heard this story before, Mike. I don't know, is this a deja vu A little bit.

But basically the Trump administration is also announcing that they're gonna do a deal that caps the tariffs on Taiwanese exports, so that at the very least, they are similar to what everybody else did. But, uh, the folks at TMSC are committing to building additional fabs here in the United States. John, I know you've been covering this whole space coastally, but, um, you know, how's it, it is all this, in the end of the day for our national security or economy, what's your take?

Sounds like a kind of a expedient trade on political basis. Like our last segment. I mean, in a sense, the idea is to reduce the tariffs on Taiwanese goods, uh, from my best 28% to 15%, which is in line with what Japan and South Korea are paying.

And in exchange, TSMC is gonna commit to building, I think four additional ship manufacturing plants in Arizona. They already have six there. Um, this would be a incredible, uh, financial commitment if it, it does happen.

And I always say if, because we look back on this and look forward, we're, they're gonna be like a thousand different variations of what happens in this situation. So by the end, we'll, we'll never know, but, uh, they're gonna de devote tens of billions of dollars that evidently to build out in exchange for this lower, lower, uh, tariff percentages. You know, and again, it's, it's deja vu right?

All over again from the last segment. Um, again, it's it on paper. This is what they're talking about.

National security be damned evidently until, until they decide to, to put a bandaid on the latest crisis. Um, I don't know. I, the, the more we look, I look at this infrastructure build out, and it's not gonna slow down.

By the way, there's a, there's a report, I think global data came out with a report about AI tailwinds and this idea that investments are gonna accelerate even more so this year than we thought. Um, we're gonna just see more of these types of deals. And the devil is in the details.

And again, I throw these numbers, I throw out these percentages. We can do this for every story from now until the end of the year. And they're all gonna change, if not, uh, if, if they happen.

So that's kind of where I'm saying I'm being very, I'm very dubious of this whole thing. You're not alone, John. Yeah, really, Alan, let me ask you this though.

So at what point is this not in Taiwan's interest? And I'm trying to scratch my head a little bit about it because, well, if we move more production to the US then at some point the value of Taiwan to us strategically declines. And maybe, you know, when China says they wanna take it back and we don't care as much.

So I'm trying to sort the sound in my head how this might all play out. You know, the Taiwan knees are crazy like a dragon to paraphrase. Um, let's look at what they get here strategically.

You like that, Sean? I liked it. I like that.

I love that. Yeah. Um, what they're getting right now is a reduction in tariffs, and that's what they want.

What are they giving right now? A pledge. This sounds like wimpy, I'll gladly pay you for that burger on Tuesday.

Right. And you know, John, I think you mentioned there are four TSMC plants in Arizona. Oh.

So they have, they have six factories and two advanced packaging facilities. The idea is they're gonna build four more chip manufacturing plants. But how many, but let me ask a question.

How many chips are they actually making in the US and what kind of chips are they? 'cause my understanding is the amount of chips they make is not maybe zero anymore, but it's minuscule. And the kinds of chips they make are second, third, two, three generations old.

These are not their good chips. They're giving us, you know, we're making the, what we used to stamp is made in Japan when I was a kid, and they're made in China, you know, the, the lower quality stuff that's two, three generations old. And and if you ask them, they'll tell you, because we don't have the workforce to work on these two nano chips and, you know, the, the, the, the good stuff.

And so you could build chips till the cows come home, yet that cow chips, um, you could build chips till the cows come home. But if we don't have the workforce to, to, and, and again, these are robotic factories for the most part, but you do need some workers there. If we don't have the know-how in the workers to build cutting edge chips, you know, what do we, you know, that's not, that's not the, the chip factories or chip fabs we're looking for, right?

So good move for Taiwan. They get what they want right now. They promised something dubious in the future.

Who knows what that'll be. And even if they promised it, we can't deliver right now anyway. Well, and what about the security angle?

What an odd of the deal. I'm sorry, go ahead. Should I Was just saying what, you know, what about the security angle too on this from, from a lot of different aspects, but correct me if I'm wrong, hasn't China like targeted Taiwanese chips and, uh, quite a bit Like, what Do you mean by targeting?

Well, state sponsored a tax phishing and whatever, um, and, and, and sort of aimed at their chip making. I mean, I believe that's right. And what, I mean, are there, what kind of guardrails are we looking at here?

If this does come to pass, you're right, right now it's just a pledge. But has this administration thought out anything regarding national security? No, I doubt that John, I think you wrote a story too that says that Chinese are getting their own semiconductor equipment together and we'll be making semiconductors themselves more aggressively on mainland China, I would assume.

So at some point, maybe they'll just wake up one morning and go, yeah, well maybe we don't care about this as much as we used to eat. They, they may not, they may not. You know, that, that's, that's interesting that you mentioned Alan.

I think when Alan mentioned about the, the, the type of chips that they would make if they, if this ever comes to pass, and these are like nominal second rates, I hate to using that phrase, but kind of down the line, ships that aren't as advanced is those that we would like to have. So in a sense, I would really love to see, and I'm gonna go back to Foxconn, I would really like to see what they ended up end up building, like the, the size of these facilities and the number of people who are actually employed and what they actually produce, because it's gonna be like vaporware. Um, I can just see it.

And they made a nice deal. I think they snookered, um, our chief executive in the office, the artist you really snooker in For, for a guy who prides himself on being, you know, the ultimate deal maker. Well, I think they pulled the wool over his eyes.

Yeah, To your point about that, they may just manufacture in the us the, the, the earl not the latest and greatest generation of processors, but you know, it was treated like a second source for the previous generation. So you know exactly what they're making and how many things actually rolling out of those factories remains to be seen. Yeah.

I I wanna say something though about the Chinese mainland, you know, people's Republic of China facilities or plans on semiconductor. This is where the US needs to walk a fine line because if you totally cut off their access to the cutting edge chips, that TSMC is fabbing a lot of times on American design, right? You cut off the Chinese access to that.

They have no choice but to build their own chip making chip designer making capabilities. And in doing so, they, you know how they are, they'll put a lot of manpower and money behind it, and it may take them a little while, but eventually it'll rival what we see in Taiwan or here in the us. Well, they steal IP too Well by, well, and some of it may, and that may be more than poisoning the Taiwanese chips, Terry.

It may be more of stealing the plans for them, but they, you still need that technology versus what we're doing now where Nvidia can sell China, what is it, the H hundred, right? Of course there's a, a 15% cut for the boss, you know, uh, uh, over there for all of the chips they sell to China. But at least it gives, it, it keeps China, you know, it's like heroin.

It, it keeps China on the drugs and, and maybe prevents, not prevents them, but slows down their own efforts to become independent quality chip manufacturers. I think the Chinese are probably too smart, right? They went through the Opium Wars already.

I'm sorry. Yeah. I Buried, I buried the lead.

I buried the lead. Um, I, I admit. Um, so these four facilities that TSMC says they're going to build, be building, they're gonna be completed sometime during the 2030s, by the way.

Oh, good. Yeah, yeah. Plumbing online soon to a theater near you.

No, but, but what your bed earlier. But, but something's clearly up with the mainland Chinese folks. 'cause they're also saying that at least allegedly, I think John, you wrote about this, but they're not gonna use Nvidia GPUs.

They're telling people not to use Nvidia GPUs in the latest generation, and they use something other than GPUs, which I guess they have more, uh, access to. Um, so ultimately, you know, it seems like they got a bigger plan going on here that goes, that spans more than Taiwan, because I think they figured out the deep seek stuff doesn't need a GPU, so maybe they don't care. I dunno, That's, that's really, yeah, you know what, and again, it, it sounds, you're right, Mike, that sounds just like China.

They, they're, they're thinking years in advance and they actually have a precise plan versus what we have, which is kind of like, uh, throw something out there, it's broken. Let, let's figure out how to fix it after the fact. You know, there's just like no rhyme or reason to what we Do.

Talk, talk about checkers versus 3D chess, huh? Okay. Hey, let, let's move on because we're liable.

I'm liable to have ice breakthrough the door here. Any second. We keep talking right there.

Oh, No, no, no, no, no, no. Let, let, let's move along and talk a little cyber. Mike, what do we got?

Well, yeah, I would just say sometimes we fail to appreciate all the efforts that the cybersecurity folks go through to protect us. And King Charles finally, you know, set an example here where he is highlighting some of the efforts of some of the folks that worked on a particular nasty, uh, campaign that was discovered. And also, well, turns out NASA sent a very friendly thank you note to somebody in Turkey who helped them find some vulnerability in their systems.

And Terry, you know, is it me or, or is there a little civility entering this whole cybersecurity conversation that might wander overdue? I'd like to think so. You know, um, it, it was, it was kind of refreshing to see some cyber efforts get the nod from some higher ups, right?

Like, uh, so, so King Charles, um, the, actually, the, the, uh, the person that, that King Charles, um, gave the honors to was, uh, not a cybersecurity researcher or really a cyber guy per se, but he was more the coordinator, um, and sort of a strategic planner behind, uh, disrupting and taking down lock bit, um, and Operation Kronos or Kronos operation, um, a couple of years ago, right? And, um, so, uh, by all he, he's the law enforcement guy by, uh, uh, training. Uh, but kind of what came out in all of this is how important those people are in the sort of, in the, the backend, right?

Who are coordinating all of these massive operations to try to, to take down, you know, ransomware gangs and, and whatever. But yeah, he, um, he's not a knight, you know, um, uh, at this, but he did receive the order of the British Empire, um, award. I think that's two notches down from Knighthood.

Um, and he was, uh, his name is Gavin Webb, by the way. We should give him his due. And his, um, he is a lead at the National Crime Agency, which kind of led that whole effort against, um, Kronos.

The other one was, um, actually, and uh, this, this, uh, where I get a little soft here 'cause it was kind of sweet. This young researcher found vulnerabilities at, uh, NASA and through the disclosure program there, you know, reported them and quite detailed reports that he gave. And so he got a letter from, uh, NASA and it said, you know, he was, he was overjoyed and, uh, he said it kind of solidified his career path right now he knows that this is where he wants to be.

And, um, and he wants to, uh, continue to, uh, be a cyber defender. And I think that's, that's great. It's kind of tracks with, and he's a young guy, you know, so it, it kind of tracks with some of the reporting we've done in the past about, uh, I think it maybe Mike will recall last week, we also had a story on, uh, uh, ransomware, gangs, recruiting teenagers, and, uh, you know, whatever.

And so a lot of the people that I spoke with were saying, you know, we need, uh, a way to funnel these kids into something that's not illegal, right. And take their talents and, and take their restlessness and whatever. And that's, you know, Casey Elli brought Bug Crowd was in Trey Ford.

Were saying, you know, uh, uh, bug bounty programs are a good place for these, uh, these people to be. So of course, when this pops up about this young researcher in, uh, in Turkey, they were all about, this is the way we engage young people and keep them from going to the dark side and keep them on a more straight and narrow, but very satisfying, uh, path. Terry, did you say Trey Ford?

Trey Ford? Did I say Tre? Yeah.

I thought you said Trey Ford from Bugcrowd. Yeah. So Re's an old friend.

It's good to hear his name. Shout out. Yeah.

No, But he's popping up quite a bit. He's got a lot to say about Always. Does Tre Trey's been on top of it now?

Bug crowds, of course. KC Ellis, I, my friend Casey, who's down in Australia, but, um, both great guys. Both great guys.

Hey, what was the, uh, the order that the, the Kronos guy got? Um, it was called the, let's see, um, the Order of the British Empire Order of the British Empire. Hey, better than the participation trophy from FIFA Other, otherwise known as an OBE.

So that's O-B-O-V-E. That's right. So he's an OBE, if not a sir.

He's an OBE Look, look for a president to be, uh, suddenly labeling himself as a security researcher. So it, It may be that if he wants to do work here, he may have to turn that award over to the president. Isn't that the mo MO?

Um, but, but Would be, I would be happy to see if we could figure out a way to, maybe we have the Medal of Freedom for citizens. So maybe there's a medal of freedom for the security experts. That would Be cool.

That would be pretty cool. It would be a little acknowledgement. You know, I'm, I'm talking about that my shimmy says tomorrow about acknowledging some of the great work our security researchers have done over the years.

Um, I wanna quickly mention NASA, though. Good for NASA to acknowledge this young man from Turkey. You know, in an age where we seem to be shunning public space works and, and all the noises about, uh, private space.

We, we sometimes forget the groundbreaking work NASA has done at places at JPL and Goddard and places like this and all of the great science. You know, it, it, I was talking to a friend of mine, Todd Vernon, who worked at NASA years and years ago, that that was the place where smart people wanted to go work. That that was where the smart people in the government were, you know, through the Apollo missions and, and after.

And, you know, it certainly had its trials and tribulations through various administrations. This most recent administration is really cut hard, but it still remains a place where the good guys are. I think for the most part, they, yes, they may not be the most efficient spenders of public money, but the, they dream big dreams.

That's right. And they, and they do the right thing. So kudos to NASA for having a good, uh, vulnerability disclosure system.

Yeah, I'll leave it at that. No, that's great. And I mean, NASA had always been sort of an envi, enviable place to work too, hadn't it?

I mean, people really wanted to work there. People really this country was really proud of nasa. And yes, they've had some stumbles, like legitimate stumbles, but they've been sort of demonized, uh, as has everybody else, I guess this this last decade or so.

Um, so it is, but it is good to see them sort of rise above the fray and recognize a young person, you know, who did something good, Absolutely Demonized by somebody who wants to have that money go to some sort of contract from the government that goes to their company. That kind of demonized. Yeah.

That kind of demonized, but you, Yeah. Yeah. Okay.

If we don't have anything else, I make a motion to adjourn our text showing gang for today. If we have a second, just following the little for a second. All those in favor following a little parliamentary order here, as long as we're talking about King Charles.

Um, John, Terry. Mike, thanks for joining us. Thank you for watching.

We've got Techstrong TV immediately following our live gang today. com. Register for the event.

Go check out all of the great future naval gazing sessions here about so many things, tech, you, you don't wanna miss it. Um, but for now, on behalf of techstrong, thanks for joining. We're out.

Hey everyone. Welcome back here to another text drug TV interview. I'm happy to be joined.

Will first timer on our show, new company coming outta stealth. All exciting, exciting stuff. Say hello to Ido Geffen.

Ido was with a company called Novi. Ido. Welcome, welcome to Text Trunk tv.

Thank you. Very excited to be here, Ellen. So, Eno, we're gonna talk about Novi, we're gonna talk about the stealth coming outta stealth announcement, but let's first talk about Ido, tell our, tell our audience a little bit about you.

Yeah, sure. So, uh, my name is Ido. Uh, I'm the CEO and co-founder here at Novi.

Uh, 20 years of experience in cyber. Uh, for the last decade I've been in executive roles in three different cybersecurity startups. And before that I served for 10 years in the Israeli security agency, which is pretty much equivalent to the NSA, uh, mostly leading strategic cyber initiatives.

Um, yeah, so this is a briefly about my background in cyber in the, over the last 20 years. So were you in 8,200 or in the, uh, different agency? Uh, different agency, but pretty much, uh, equivalent.

Yeah, we work a lot with a 200. Got it, got it. No, we've, well, you know, when you cover the cyber market, when 40% of all the cyber VC money is being poured into Israeli cyber startups, you get to know all the different, all the different players and places where, where they're coming from.

Um, but you know that, that's a great thing. So this is your first startup that you founded, though? Yeah, it is.

Yeah. I always like to ask this question of first time founders, especially. 'cause you know, it, you don't wake up one day and say, yeah, I feel like starting a company today.

You know, you, it's, you gotta kind of feel it in your, in your gut to, you gotta have that fire, that passion that you, this has to be done. It, it needs to be done. It's gonna make the world better for you.

What, what was that passion? Eddo? Yeah.

Uh, what question? So, for many years, uh, gone and oer, my two other co-founders gone, by the way, was in a 200. Uh, and OER is a program graduate that was, uh, a team leader in my group in Israeli security agency.

So the three of us are very good friends for a very long time, for more than 15 years. And we always played with this idea that we will, in the end, we will initiate a company together. And September last year, it was the first time that the Open AI released oh one, the first reasoning model.

And we are as a three geek guys, like just read all of the specification card of it and was pretty blown away about the capabilities and, and what we think that could be done with this type of, uh, new type of technology. And we started to connect to, to oh one, the, the, the model, uh, techni, uh, tools that are specifically in, uh, um, tools that we used in the past in order to hack into specific applications, adding our knowledge and techniques into prompts way, and, and adding, uh, good examples. So that's, uh, like a knowledge base that we've added to it.

And we've witnessed that we are very, very quickly being able to do, uh, and find novel issues, novel vulnerabilities and applications. Something that couldn't be done before in automatic way. And this is, was like our aha moment that none something fundamentally changed in the ability of, uh, on how to conduct a penetration testing.

And this, this is the way we felt that this is our moment, is there is a very unique technological shift that we have a very unique expertise and a very big pain that is just going to grow on the, the customer side. The, because the, the, you know, there is much more code now that is generating by ai, much more applications and much more vulnerabilities that you cannot continue and just do it like, like penetration testing is being done today, only point in time in a manual way. Got it.

You know, you know, I've been in security 25, 30 years. When I first started, one of the companies I co-founded, we, we were, one of our products was VM vulnerability assessment of management. And back then, look, it was, uh, it was difficult to get people to at least scan their networks once a year, let alone quarterly, monthly, weekly, continuously.

You know, it to the idea of being able to do that or that you should do it even, you know, it was foreign, was foreign to most people. Now, I remember when, uh, me exploit first came out, right? In HD war, I'm sure you probably have heard of HD and, and everything.

I know HD for a long time, and now we had the ability to do AppSec scanning, penetration testing. But again, it was, it was a tool used by consultants. You would call in maybe a red team or, or something, right?

Again, but once a year to pay, if you were a big PCI, you know, merchant maybe a little or more often, when do you think we, we cross the Rubicon from once a year or once a quarter to continuous testing? To continuous security scanning? So I think that, you know, what would happen until today is that you have a real technical barrier that you couldn't do this type of testing in continuous way.

Um, and one of the reasons that you asked also before, you know, when we started to initiate the company, so we spoke with different, uh, CISOs and, and security practitioners, and we got a lot of people that are saying to us, especially in organizations that store sensitive data, and they have, you know, that the, the, the product applications that they're developing is the core revenue making of, of the, of the company that they're telling us we want to, to do much faster, deeper, wider tests. And they told us, for example, that, um, that they want us to do it in, in a daily basis because the, the, the way that Code ships today is in continuous way, right? You have the CICD.

So I think this is the right time for us to, that, to eliminate this pain currently, that really security practitioners need to choose between two bad options, continuous tools that works in continuous way, which is great, but provides very shallow insights and tons of false positives or manual penetration testing that provide novel insights sometimes that it's really just point in time. So at least from what we are feeling today from the market, there is a need and a lot of requests that even not doing the test only once in a month, but can you please connect to our CICD and then we will be able to test the Delta and every new release you will be able to do full blown penetration testing. So I think the, the time is now and, and, and the urgency is just getting bigger because today a developer's, you know, utilizing more and more AI tools for developers and you even have vibe coding.

So it's just exploding the, the amount of application that, uh, enterprise today are generating. So I think that this is the right time for it. Agreed.

So I think it was just yesterday, YL Ventures, one of the first Israeli cyber venture funds, pioneered that model, uh, released their annual, uh, venture report on the state of Israeli Israeli cyber. You know, it is pretty eye-opening, right? The amount of money, the amount of companies, the amount of exits, serial founders, everything else, but even in light of that, right?

You guys are launching from stealth with a a really, I mean, a seed round. That's pretty remarkable. Not the biggest ever.

I I saw it. You know, they've, lately we've seen some crazy seed rounds, but tell us a little bit about, uh, your seed round here, Novi seed round. Yeah, so first of all, we were lucky, um, because Ventures is one of our, it's, uh, the seed investor and also Cannan partner, uh, which is also invested in a lot of e early stage in early stage Israeli cybersecurity startups like, uh, Snyk and others.

Um, and the fact that we had such a great VC that have a very good experience on, you know, are we in product market fit, and the fact that they've seen that how quickly we were able to generate revenue and dozens of customers, and how quickly we're getting those, this is what, so the, the, it came from them, the, the fact that you should hire, you should raise now much more money in order to, you know, to, to take the advantage that you currently have and, and the pain that is really, uh, vivid today in the market. So you raised the money and congratulations like a $51 million plus seed round, um, beyond it's a lot of money. What does it mean in terms of accelerating product plans, accelerating go to market for Novi?

Yeah, great question. So we understand that in order for us to be one or two, three steps before the bad guys, we need to build something unique with a real mode that it's hard to, for, for, you know, just, uh, you know, for any other attacking group to be in our level. So the fact that we raised so much money gave us the ability to raise, uh, to, to attract the best talent in the world in cyber, but also in ai, we have PhDs in our team.

We have the guy, the head of AI in our team. Dan Padnos was a VP of platform in AI 21. So he literally built a model that tried to compete with chair GPT for seven years.

So this is what gave us the, the confidence that we don't just another wrapper on top of chair GPT, we are building our own proprietary, uh, model that is specialized in cyber. And we already, uh, seen some tremendous results even comparing to Gemini and Claude that for specific types of vulnerability, we already have 55% better results. And so this type of money and the ability to move very fast and to really attract a very unique talent, uh, this is what we think, what give us a good confidence that we will be able to build something that is much, much better than all of the bad guys, uh, and their ability.

So we will be faster, deeper, and wider on protecting, uh, our customer. You know, uh, this week actually the 15th, we have our Predict 2026 virtual event. And, uh, we've got all of the FU analysts talking, but this is something we spoke about in the cyber session there, which is for 2026 and beyond, just using the frontier models by themselves is not enough to really do security.

Right? Right. Because you gotta remember that those front, those frontier models are as good as the, the information, the data they're trained on, and they're trained on.

They don't call 'em large language models for nothing, right? They're large models, but they're not that specialized, right? Remember that 90% they estimate of all of the data that's digitized is behind firewalls, was not used by these large models to train.

And so the future is, you want to call 'em small models, you wanna call 'em, uh, you know, vector databases that are in front, or we are Calling it purpose trained AI model purpose, Okay. Purpose trained AI models, right? That's, that's where the actions gonna be.

No one's going to do highly specialized work just on a generic frontier model. Agreed. Agreed.

I, I definitely agree that a lot of the, the challenge also when you're building this type of model is exactly like you described, is ability to create a lot of synthetic data and simulate those type of attacks. Um, and this is exactly what we are doing. And also those large language models as you described, there are good in, in, in everything, right?

On how to cook a, a dinner and, and how to answer early generic questions, but they're not specialized in taking forry knowledge on finding issues at, at, at, uh, at applications, or even more importantly, on how should one fix, mitigate or remediate security issues. Sure. Um, yeah.

So all of the external context that they're missing, Agreed. Um, let's talk about go to market a little bit. So how, how do people sign up for Novi?

How do they get started? What does the cost, you know, what, what's that all look like beyond, beyond the technology? Yeah, so starting us with us is, uh, I'm calling it, we have a pretty no brainer, uh, proposal, meaning that you can just come to our website, Novi security, uh, book for a demo.

And, and basically that's it. I mean, after that, signing an NDA and we can start a POV and out of the unique proposal that we're saying to people, at least now that we are in the early stages, is you are already paying for penetration testing. You already have budget for it.

We are the best penetration testing company in the world, um, so we can do it. So we, you can replace this budget with us. And by the way, we also can replace your dynamic application security testing, the DAF tools, the vulnerability scanners, um, and we are coming from the outside.

So some organizations have external exposure tools, so we can replace the traditional scanners and the manual penetration testing, uh, in one bundle that gives you the best from, from both words. Um, but really the deployment is just signing an NDA, giving us an access to the application that you liked us to test. And that's it.

So this is what makes us move that fast, is the ability to very quick deployment. And in a matter of less than a week, you're getting an access to the user interface, seeing all of the unique issues that we were able to detect. Um, and most of the time that this is pretty enough for, okay, let's, let's now work together in collaboration.

Who, Who would you say the, the average the target customer is? So we are targeting at least medium size and above organizations. Uh, we're not customers that, or, uh, organizations that are doing penetration testing just for compliance.

Those are not our, uh, ideal customer profile. We really look for organizations that sees themselves as a target, and they really care from the security, uh, of their applications, and they, and they want a prime, uh, results. This is what we are providing.

So, Got it. We're about outta time, but I wanna make sure we hit this NOV security, N-O-V-E-E Security. Yeah.

If you Go sign up and start, you know, as you said, sign VA and get a, uh, a, uh, a, an instant going and see how it goes. Yeah, definitely. Excellent.

It's, uh, I Mu congratulations. You know, mazel tough on the, on the raise. Good luck going to market now.

Right now it gets fun. Yeah. Yeah, it is.

Now, now they game me on. Definitely. All right.

Edita Geffen, CEO co-founder at Novi at Novi Security, continuous AI powered, uh, pen testing and more all your security testing right in one place. We're, we're gonna take a break here on text on tv. We'll be right back.

ai Leadership Insight series. I'm your host, Mike Baard. Today we're with Alex Victoria, who's CTO for Zen Business, and we're talking about, well, how AI will be applied to small businesses and how it can maybe help them compete more effectively against the big guys.

Alex, welcome the show. Thanks for having me, Mike. Good to meet you.

So maybe level set us a little bit here first, but what is fundamentally different about using AI in the context of a small business versus what we might have seen in these larger enterprises where there's a lot more resources? What do they need to do to kind of turn AI on and actually, you know, leverage this? Yeah, there's, there's really two, um, two different ways I think about it.

For, for Zen Business, our goal is to really, uh, help very small businesses get up and running and get started from the beginning. And a lot of our customers are first time business beginners. Um, and that, that, that journey is a complex one where you ha you run into many, many different complex questions throughout the beginning of the process, but even after you've got your business up and running, there's a constant kind of barrage of work that the, the, the entrepreneur never thought they would have to do.

You know, a lot of these folks thought they were gonna get to do a side gig with their dream, but instead they spend 70% of their time making sure their accounting books are correct. Uh, and so, you know, Zen Business has always, even before this AI boom, been focused on that problem. Uh, and so what we're really trying to do is leverage AI to get, to make all that easier for the small businesses to get started faster.

The second way I think about it is, how are small businesses going to leverage AI to deliver their products to their customers? And that's not so much what we're focused on at the moment. Um, although I really do think that's where we head in the long run, is that we start using something like Velo.

Our, our personal AI assistant for small businesses. We like to think of Velo as kind of like their co-founder, productivity partner. Um, I could see in the future where they're using velo to like, operate things inside of their business as well, um, or, or other AI platforms.

So it's really, it's really, um, either of those, our focus today is really on, on them operating the business. Alright. Well you mentioned Velo.

So yeah, for the uninitiated, what is Velo exactly? So Velo is, you know, our vision with Velo is that it's the productivity partner, co-founder for the small business. And then it begins your, with your journey, uh, from the day you start interacting with Zen business.

So the majority of our customers are people who are al either already working or already have a business that are starting a new one. And so they'll find us by way of Google or something like that. From that moment we have Velos sitting there with them, uh, helping them research.

So the other thing is a lot of customers will spend sometimes months researching what to do with their LLC, what state to put it in, whether they need a DBA or not, what accounting software they should use, what their website should be. There's a lot of these questions that they have to answer. And a lot of times they're using sources from all over the internet, jumping around and doing all this research maniacally.

'cause it's scary. It's a scary decision to get a business started, especially when you've never done it before. And so the idea from when you get the Zen Business Velo is there from the beginning, you can, you can use Velo for free and you can research all the different options of your business, uh, needs before you get started, right on Zen business.

And then it follows them down the journey. So they can create an account with Velo and use it for free just to do research. We'll, even one of the things Velo does is it'll even tell you who our competitors are.

And while you might wanna pick one or the other, the idea is to really just, uh, help the consumer make the right call. And of course, we want them to choose us 'cause we think we're the right call. Um, but we wanna be honest with them too.

Uh, the next step from there is if they actually decide to start with Zen Business, then they end up with a full account and velo. But at each, each one of those steps throughout the way, Velo is learning more and more about them, their desires and what they wanna accomplish, so that by the time they're up and running, it's got all the context already. And that's, that's allowing us to do things like, say, you need to file an EIN Velo can fill the form for you because it knows so much about your business already.

Uh, and, and that's just one example of what's coming in the next couple weeks. But there will be a long line of these, like all this kind of operational filing stuff, your annual reports, all the things you have to do around kind of keeping your business compliant with the state. Uh, ve Vela is gonna be able to do most of that for you.

Um, and today, today the customer has to go click like through a 30 page form filler and enter all these complex details to get these things done. But by the time they've getting gotten to the point through us, we have collected all that context and can make things, these things happen faster for them. Um, so, you know, velo, like when a tax season's coming around, Velo reaches out and says, Hey, it's tax season time.

I know that you own an Italian restaurant in Austin, Texas, and you've, your annual reports are due on this date. And you have, because I have access to your accounting software, I can tell you what your next steps are on getting your taxes prepped and all that kind of stuff. So will it generate the annual report that I might not need to file for the small business based on what it knows about me?

Or how far will it go? Well, today, it's, it's not gonna get, you're, you're gonna have to tell it to finish. You know, it's not just gonna go do it, I don't think just yet.

Um, but in a lot of cases, you know, the backend of our filing systems are automated as well. So we, we do foresee a point where velo could just know its annual report season, prepare your annual report, send you a note and say, come hit okay on it. Uh, and, and the thing is, annual reports are quite different in every state.

Some do them in different, they have different purposes and at different times of the year. Um, but it could certainly have it ready for you. And when you say, okay, then automation on our backend is also, uh, doing it quickly for you.

And so that's the vision is that, um, in this space, we've, we've been challenged with combining technology and, and people and AI has become this, this thing that is allowing us to do it more effectively. Uh, and it's, it's, it's just turning up the automation opportunities to the roof for us. And then what we're learning is how to inf help our customers.

You know, the next step is like, how to figure out how to get them to do it too. I truly, personally believe that like the small business is probably the primary way for the average am average American or average person to get their piece of the AI boom. You know, I don't want to get like philosophical, but you know, a lot of wealth is accumulating in, in, in a small number of places.

Um, I actually think this is a better time than any for people to start a small business because they're gonna get to use AI to make it more effective for their customers. So it's an exciting time to, to be where we are. We've been slogging at this for seven years and it's, it's all of a sudden, uh, I think we're at the point where we can actually achieve our dream, which is the, is to be the most effective as possible to help our customers make this decision that gets started.

'cause it's a scary one. And we believe in entrepreneurship and everybody having a chance to be their own boss. What's behind the platform exactly.

Is because I don't think, did you build your own foundation model? Seems unlikely. So what is No, you guys working with here and how does it Yeah.

What come together? What I tell it's funny, people ask that, and I tell 'em investors, I'm like, well, if you gimme a couple billion dollars, you know, I'll go, I'll go make a model if you really want us to differentiate. Um, but no, we don't need to do that.

In fact, velo velo itself is a, a fairly common public pattern that we've written about on our tech blog as well. Um, it's a, it's an, um, a coalition of routers, a agent, a coalition of agents within a routing agent that, that decides how to answer questions or do tasks for a customer. Each of those is dependent on, uh, prompts and a bunch of tools.

So what makes Velo different for us is that it has our knowledge base, which is really every detail of everything a small business would need to know in all 50 states. Plus, uh, it has access to our tools, which are all the different platform APIs we apply. So we have your website, bank account, domain names, uh, uh, accounting software, and then all the compliance and formations needs as well.

Uh, and so all those put together, uh, allows us to do this. Um, the model part is interesting. So one of the things we did early on was we decided to centralize LLM usage in our platform.

And so we have a central part of the Zen business platform that obfuscates the details of the different providers. So we use Google, we use OpenAI, we use Anthropic depending on the task. And, um, we can change those on the fly if needed.

Um, and we've had to do that, like all of a sudden Gemini has a problem. We switch it all over to OpenAI as a back a backup thing that we wrote about that on our, our tech blog as well. But another crafty thing we've done, 'cause people get concerned about the cost, is we use the real, we use very old small models.

So like we're using the Gemini two oh flash for like, most of what we do. And then what we do is when there's a, when there's a certain case that just needs the additional logic, we can upgrade it to like, say, go use open AI four oh or whatever. But we, we, we avoid the, the biggest, most effective, most expensive models, kind of like the plague.

Mm-hmm. And what we're finding is, you know, for most of what we need to do, we don't, we don't need them. So we like the ability of not being locked into one vendor.

We can switch back and forth and, and honestly, they all, they all are producing really amazing technology that it works. You know, it's, none of this would work. The real, the real, the real thing we learned was that tool calling the model has to be good at calling tools and, and we solve a lot of problems with tool calling.

Do you think as we go along that, um, small businesses typically interact with other small businesses, and if we're all gonna have our own AI tools and AI agents at some point, you know, does my AI call your AI to complete a task as a small business? Or how does that play out in your mind? I mean, I think we'll inch towards that.

Uh, it's funny, I think of years, even, even when this all started, like a year or two, a couple years ago, we were like, pretty soon recruiting is just gonna be like, you know, the, the hiring person's AI talks to the candidates ai, and they just, they make a decision. I don't think we're there yet. Um, I certainly think AI can facilitate the communication between the two.

That's like a no-brainer use case today. And that's actually where most of the real value I've seen is coming from these AI products is like customer service. You know, that, that it's things that are heavily, uh, layered of upon people talking to each other can be facilitated by ai.

So I could see AI going, you're about to do a deal with so and so, and we're gonna redline the contract and back and forth it between two ais and present it to both of you at the end and say, this is, this matches both of your needs. Like hit hit okay to go. Mm-hmm.

Um, we, I, you know, that's, that's, that's, that's here we could be able to do that today if, if someone wanted to. Do you think small businesses are prepared for this scenario though? 'cause at some point their customers will also have AI agents.

Yeah. And those AI agents will be optimized to maybe buy something at the lowest cost possible, and your AI agent is optimized to sell it as the most profitable way possible, and the two of them will battle it out somewhere in the ether. Yeah.

I mean, I guess supply and demand, that's like the, the purest form of supply and demand curve is mm-hmm. Two algorithms go until they find the happy point and go. Um, yeah, I, I think certainly it could be facilitated by that.

Um, it, it's a, you know, we found that like a lot of our customers, the ones who aren't in technology businesses, uh, managing all this stuff is quite complex. I mean, e even even for like, you know, entering your expenses and having the time to even go log into something every day and make sure you uploaded your receipts for your, uh, for your expenses, that, that, that's challenging for a lot of the folks. And so I do think there's gonna be some work to figure out how to make them able to use this technology because it's, it's pretty complex today.

I mean, we we're lucky to have a, a bunch of really smart, uh, product development people at Zen Business, um, and, and you know, Google and Anthropic and those guys have everybody else. So I, I don't know how the, you know, right now, the average small business that doesn't know how to wield this stuff is, it's gonna be hard to figure out. So that's where I think there's an opportunity for us in the future and somebody else to help.

I also think, you know, all those engineers that people say are having trouble getting jobs, I think they, they have a lot of value if they know how to wield this technology. Um, I was telling my nephew who just gradu is graduating from college this year with a CS degree, I was like, you know, if you learn how to use this stuff, you're gonna be really valuable. You know, so, because I think it's pretty hard to be getting a job right now, and Well, to that point in the societal impact, right?

So we're seeing it's harder for, uh, new people that get hired into a space than ever. It doesn't matter what the vertical is these days. And we're also seeing more folks get laid off because companies are thinking they're gonna automate certain things that they used to hire people to do.

But does that create a larger pool from which we will see more small businesses start to emerge and people will be able to engage in that activity because the complexity of starting a business is dropping? Yeah. And that, I, I agree with that completely.

Um, I think, well, I, one thing I don't, I don't necessarily think they're all getting laid off because of ai. I think maybe they overhired and there's just a reckoning happening. Um, but there, I do think that, uh, that's gonna be a way for people to benefit from all this, and it's gonna be easier than ever.

And, and honestly, when we started Zen Business, one, one of the ideas was that, uh, the, the barrier of entry for starting a business is lowering because of technology. And particularly at that time, it was kind of SaaS technology. You don't need the firm anymore to get a business started.

You don't need to hire 10 people. You could get online and start taking money and put a product together and sell it. And you could do that all yourself with technology, AI is like the next evolution of that where, I mean, you could build your, your product with cloud code if you, if you knew how to wield that thing a little bit.

And that's why I think, I think, you know, I, I'm very passionate about those agentic development tools. They work and it, uh, people should be committed to using them. We use them a lot.

Um, they still require a technology person to run 'em though, you know? Mm-hmm. And I, and I think that's gonna be the case.

And I, uh, one of the ways engineers can get a lot of value in their careers too, is learning how you still need to know how to build software ultimately to build something complex, you know? So do you think small business owners will develop something that feels like a relationship with these AI agents and maybe even getting the name? Or are they gonna be more, you know, seen as disposable kind of software widgets and we're not gonna get that emotionally attached to them?

That, that's an interesting idea. I'm trying to think of, the way I use, the way I use Chad GBT is I have, I have like dialed that thing in to, to be like, really, um, personalized to the way I like to communicate when I'm using the voice mode. And I, I, you know, I, I don't want any fluffy language.

I've come up with all these prompts that make it say as little as humanly possible, and it just treat, I want, I'm like, I want you to treat me like a robot. Just like, say things you know, don't. And, uh, and then I even picked the voice and one day I was using it and my wife was like, did you ever notice the voice you chose?

Sounds like me. I was like, I don't know. I, maybe I did.

I don't, I didn't do that on purpose. But yeah, I think people are gonna wanna personalize their experience if, especially if they're com communicating with voice, which is right around the corner for us. Uh, we're, we're gonna enable that sometime soon.

And I think a lot more and more people are talking to these things. I think you're gonna want it to kind of know who you are and know how you like to communicate and probably give it a name. I mean, I would, I'd, I'd, I'd love to high if it was running my business for me, I'd be high fiving it.

Like, if I could high five cloud code, I would, yeah. Cloud code's amazing. Well, maybe, you know, you're gonna do what the agent says you should do because it sounds like somebody you're already listening to, right?

Well, yeah, there's, there's a lot of like, futurist thinkers saying, agentic CEOs are around the corner. So I could see a world where you've created your own agent to just kind of manage you day to day, and you're just doing what it tells you. But of course, you created it.

There you go. If you don't like it, you can veto it. Yeah.

Um, so as you look into 2026, you know, it's a new year, what are you excited about? What do you think we're gonna see next? Well, I mean, for Zen business, you know, like I said, we've always been in this spot of just trying to make it easy to get your business up and running and then run it.

Focus on what you love to do and make some money and be your own boss. Uh, I think for the first time, velo, you know, having the technology in place to deliver velo throughout that experience is the most exciting thing I've, uh, I've, I have going for me. Um, you know, and then also when we started Velo, we really made the choice to, to kind of learn in, in public and write about it on our tech blogs.

So, uh, I'm, I'm excited about, you know, showing off the talent we have in the team, but also giving back to the folks that, you know, put some of these things in place to get us up and running. And maybe, you know, some of our customers learn from it too, uh, and I think, uh, we're gonna, we're gonna really accelerate what we can do. The other, the other learning that we've had is, like, our velo team has only been around for a couple months, and when you know how to leverage this technology in the right way, they've, they've delivered at a rate that is way higher than traditional engineering teams.

And so I think we're gonna see an extremely fast pace, like feature roadmap, you know, Ave is gonna do more and more and more and more every day as we continue to focus on it. And, and, you know, that's probably true of anybody who's building an age agent system like this. So, in terms of like the macro view, we're gonna get a lot of software.

You know, we built, we have this internal system. We built a very complex management UI for it with, with cloud code, and, uh, you know, with automating engineering pipelines. And of course I had to like, take care of it, but the thing it built was so complicated, it actually made me think like, do we really need to build this?

And I think that's the world where getting into, like, you can literally build anything you can think of. And if you can, and you can do it with a low number of resources, except you gotta pay anthropic, open AI or Google, uh, and, and you maybe open source models get to a point where you can just use 'em to do it too. But if you can build anything you want, I think that's pretty exciting world.

You know, like, yeah. So I, I think it's gonna produce some cool companies and cool businesses small and large. Alright, well folks you're hearing in here, Hey, if you're outta work or you're just playing fed up with your existing job, go start your own company.

'cause it's gonna be a lot easier to do than ever. Hey Alex, thanks being on the show. Yeah, thanks for having me.

All right. And thank you all for watching the latest episode of the Techstrong AI Leadership Insight series. You can find this episode and others on our website and invite you to check them all out.

And until then, we'll see you next time. Hey everyone, welcome to Still Cyber. I'm Alan Shiel.

And I'm Mitch Ashley. And we've been doing this a while. Still.

Cyber Baby, Still Cyber Mitch, it's good to see you. Happy New Year, man. Happy New Year.

And, uh, you know, chalking up another circle around the sun and, uh, we're podcasting it still, so it's awesome. Still, Still, still cyber still podcasting. Hey, I wanna welcome our guest for this, uh, episode of Still Cyber.

Her name is, or slo, uh, or is an analyst with YL Ventures, or welcome to Still Cyber. It's great to have you on here. It's great to be here.

Ellen and Mitch, thank you for having Me. Thanks for joining us. Appreciate it.

Yeah. Um, or before we jump into stuff, if you don't mind, give people a little bit kind of, of your background, your journey to being an analyst with YL and though I look, I, I remember when Y first started ell to tell you the truth. Mm-hmm.

Yeah. Um, you know, Mitch, you hired that old, but for people who maybe don't know ell, maybe you can give him a quick recap of that as well. Yeah, for sure.

I, I'll start for, uh, for my background. So, uh, so I'm an analyst at 12 Ventures in the past, uh, two years. Uh, I live in Tel Aviv, uh, like, uh, all of the cybersecurity tech people here in Israel, right?

Mm-hmm. Um, so prior to that, I served in the 8,200 unit. Um, then I operated in several startups, uh, here in Israel, uh, as a security research security.

I held security research, security analyst, uh, positions. The last role was in the incident response department at Signia Signia Consulting. Uh, it's a company providing incident response, uh, service services, uh, I assume you've heard about it, but not in a best context in the past, uh, in the past couple of, yeah, yes.

Offensive security and stuff like this. Yes. Yeah.

And, um, uh, it's, it's an amazing company, uh, which exposed me to, uh, the recent, uh, trends and attacks, uh, right. Uh, companies are coming to, uh, to respond to incidents where the security stack failed to perform. So I was in this interesting interject, interjection, sorry.

Um, and yeah, I kind of did the shift left in my career when, uh, when I chose to join Wild Ventures to see where the magic, uh, begins, uh, to invest, invest in early stage cybersecurity. Yes. Well, So the, the YL ventures, if you don't mind me jumping in mm-hmm.

Really sort of pioneered the, the model of investing in early stages, Israeli based companies Yeah. With an eye towards helping them migrate or penetrate the North American, European, you know, rest of world market. And oftentimes that meant that at some point, some of the executives, maybe the sales and marketing team would, would be based in the us whether it was Boston or, or, or Silicon Valley or what have you.

But r and d engineering research usually stayed in Israel, and that's also one of the very popular model, very successful, first, very successful theme-based, um, yeah. Venture funds centered around that as well as Security. Yeah.

So yeah. So, so also security only. Yeah.

Yeah. So, so, uh, so, so what you described, uh, really relates to, to well ventures and how, how we operate. So, while venture has been around since 2007, uh, we're, uh, uh, top Israeli cybersecurity, uh, uh, vc, uh, in Israel.

Uh, we invest, uh, early stage, uh, seed investments in cybersecurity, as you said, uh, Israeli entrepreneurs, uh, only, uh, we're investing from our fifth fund, uh, now, which is, uh, $450 million. Uh, and, uh, what, what, what our expertise, what we bring to the table is our value add, uh, um, uh, program, which is, uh, here in Israel, we are responsible for investments and deal flow and, and, and pursuing new investments, but also supporting companies, uh, sends the minute they get their, the, the check that they, they put the money in the bank. So we support them in, in product market feed, in marketing, in in hr, recruitments in operations, everything they need here in Israel.

And also we have, um, uh, uh, sites in San Francisco and in New York also that are responsible for this exact, uh, business development and to keep nurturing our, uh, uh, great network of advisors, security practitioners that help us and advise us and our portfolio also. So the model of, of, of a typical, uh, cyber security startup also apply, uh, to us where the, the development and, and, and, and r and d sort of is here in Israel and the, the business and the sales is in the US also. Excellent.

Yeah. So, or you know, it's a great model and Vin the team has done, have done an amazing job. We wanted to talk today though, about this report that just came out.

Mm-hmm. Right? Um, kind of, and this is not the first year, I don't know how many years why I was doing it.

Uh, maybe you would know, but it, it's kind of, this Is the 10th edition, Alex, the 10th, 10th Edition's, my god, 10th Edition. Yeah. And it's kind of the state of the Israeli cyber investment scene, if you will.

Yeah, Yeah. Venture scene. Yeah.

Um, people can get it from the YL venture site if they go. Mm-hmm. But, or we don't have to dive really deep, deep, deep, but give us kind of the highlights, if you will.

Yeah, for sure. So, so as you mentioned, uh, the report is called, uh, the State of the Cyber Nation. Uh, so basically we, we've been collecting data throughout the entire year, and we released a report in the, in January of the following year to provide the most holistic view on what happened in Israel in cybersecurity in the past, uh, year.

Uh, we collect data up until the very last minute of the very last day of the, of the previous year, because I don't know if you've noticed, but December was, uh, was crazy in, in terms of funding in MNAs in Israel. So, uh, the ecosystem never rests, not even in no, uh, in, uh, holidays, in US holidays, Uhhuh. Um, so yeah, we collect the data, our position in the very core of the cybersecurity ecosystem expose us to, uh, to, to everything.

And we are able to provide the most accurate numbers and also insights and our projections for the following year. Um, so yeah, let's, let's talk about it. It's the 10th edition.

And, and, you know, I I I, I've been living in the data in, in the past, uh, weeks and, um, and, and so, um, um, you think that you have, that, you have a gasp of, of that the ecosystem. You, you get it, figure it out, and you know what's coming and what happened. And the numbers surprised even myself in, in the best way possible.

Um, this was the most active year in Israel, uh, in terms of funding and, and, and money entering here. 1 billion, uh, entering Israel, uh, over 136, uh, rounds, uh, which is the most rounds we've seen in the past decade. This is amazing.

And also, uh, we talked about it, uh, before that, uh, uh, 40% of all cybersecurity funding in the world, uh, was invested in Israel. And when, when you look at, at, at the map of the world, Israel is like a dot of dirt. Like w we are so small.

We are so small. So this is absolutely incredible. Uh, and I'm so grateful to be part of it.

Um, and, and we Can, you know, one of the metrics or that that Yeah. I saw in the report, and we were talking off camera that I think really capture it is yeah, 40%, and if I'm wrong, correct me, 40% of all of the venture capital invested into cyber companies in 2025 went to Israeli based cyber companies. That's amazing.

That's unbelievable, Right? A country, the start size approximately of the state of New Jersey here in the us Right? 40 40, nearly half of all the cyber funding in the world.

Yeah, Ellen. And, you know, I think, I think, uh, our size is also our biggest trend, uh, because we talked about a little bit about, uh, why this is happening, how are, how is Israel so strong, uh, in cybersecurity and why everyone are so eager to start their own companies and, and also are able to succeed and, and create category leading companies in cybersecurity. So, um, uh, I I I, I welcome you to, to come to Israel and, and walk the streets of the Tel Aviv and see the magic happens.

Yeah. No, I've been there five or six times. I, I, I'm well aware.

Um, and I have so many, so many friends, not just actually in the cyber market, the cyberspace in Israel, but the, the DevOps community there. My friend Hir Heitzman runs the DevOps Tel Aviv DevOps community. It's also a vibrant, vibrant rich community.

Yeah. Not as much as the cyber, um, but you know, Mitch looking at one metric, the investment, the VC investment mm-hmm. Let's call that money in, but you also gotta look at money out.

What if like, the exits this year, right? Well, you have The Wiz is a $30 billion, what is it, 32 or $36 billion 32, I believe. Yeah.

But Yeah, exit. So that's certainly a, it's kind of a gravity, well, a gravity sinks that, that kind of brings it up. But it's not just the wiz, how many, and I, I believe it's in the report or mm-hmm.

How many exits or liquidity events, uh, also in the, in this past year from Israeli based cybersecurity companies that were, you know, involved in m and a, uh, activity. Yeah. Yeah.

So, so we've seen a lot of exits also. And, and what's also surprising in, in this m and a activity in, in 2025, a trend that we've seen starting, uh, last year and and has been accelerating this year is, is the fact that, uh, Israel cybersecurity startups are acquiring other Israeli cybersecurity startups, like consolidation within our ecosystem. So this, this represents, uh, I think like, um, um, a mature and independent market.

Uh, you've seen companies like Cato Networks that acquired, uh, aim Security, our company, this was our com portfolio company, a aim, security, security for a, a company, uh, got acquired by Cato this year. Um, yes, Sierra that acquired also a Israeli company, uh, sending one that acquired from security, like big category leaders that choose to, to acquire Israeli startups within the ecosystem. Uh, we haven't seen, uh, uh, a lot of, of those activities in the past.

And now in 2025, we've seen 12 of those acquisitions. Um, I think that's to go back to back, to go back to, uh, to what we talked about earlier with, um, this is a proven market. This is no longer the, the startup nation.

We're the, the scale up nation. Uh, everybody, uh, believe they can build the next wheel, the next Sierra, the next armies. Um, so, uh, there is also an ecosystem of, uh, second time entrepreneurs or, or serial entrepreneurs that are investing in new entrepreneurs, mentoring them.

Uh, this is a, like a cycle and never ends of, of, of nurturing and mentoring, uh, older entrepreneurs, new to new entrepreneurs. This is what fuels this ecosystem. And also the proven, uh, exits, right.

With armies, uh, CyberArk. Yeah. CyberArk also is this year mm-hmm.

Plus arm. Mm-hmm. That's a good point.

Yeah. Yeah. Um, you know, we, first of all, look, I encourage anyone watching or listening to this go, go download the report.

See for yourself, the numbers are pretty, for sure, eye popping. But let, let's go beyond the numbers. Why, why, you know, look, the whole, you, you could say the whole idea of how Israel was founded as a modern country, country, not company, a country in 1948 was a bit of a miracle in itself, right?

There's a whole story, there's movies about it and everything else, but it, there really, there's a method. There's a, there, there are several reasons why. Yeah.

I think we, we see the Israeli cyber market cyst ecosystem community be so strong. Mm-hmm. And it, I, I think it, you mentioned your former 8,200.

Yeah. And I have to apologize, is there a unit 8,100 in cyber two, or is it just 8,200? There is a 8,200 unit, and there is also a unit called 81.

Right? Eight one. Okay.

Eight one. Okay. We, we, I met people from both.

Yes. Yeah. Okay.

And that's why I always get confused, but you know, for those who look, most people I think in the cyber world have heard of it. For those who haven't, it's, it's kind of the Israeli version of the NSA, if you will. Mm-hmm.

Here we have the National Security Agency, uh, but you know, it's a cyber unit that's responsible for both offensive and defensive cyber operations. And, you know, and the, and the IDF has a world renowned reputation for being one of the best, not the best, when, when it comes to cyber. So, you know, a lot of, a lot of the Israeli cyber talent comes out of those, those units.

Yeah, For sure. However, That's not unique to Israel, right. We have the NSA here and the NS a's big.

There's a lot. Mm-hmm. The NSA has a big budget.

There's some of the smartest people in the world. I know. You know, I've, Mitchell and I have been to fort me.

Mm-hmm. And, uh, you know, we, we know the kind of people there, but not just the us European nations, uh, Asian nations. Every nation today has to have a cyber unit, right?

Mm-hmm. And, and, and a lot of these nations are a lot bigger, have more budget, have more people. Yeah.

What is it about the 8,200 or the IDF system or the Israeli culture, or what is it that Yeah. It has helps you sort think it's come Together. It's all combined.

It's all combined, right. You know, uh, the, the usually mental mentality we are, uh, restless. Uh, no, but, but, uh, jokes, joke aside, I think that, um, I think that the, the mentality in the 8,200, uh, unit in those cyber units, um, is that there is nothing you can do.

Uh, we are, uh, we're in a, in a complicated, uh, uh, geopolitical area, right. Uh, to be gentle. Mm-hmm.

And, uh, we need to, to protect ourselves, and we need to, to, to innovate and find ways to do that. So the innovation and the, the innovation mentality starts as early as, uh, in the army, uh, where you, you need to find ways to, to, to innovate and, and to be the best and, and to protect yourself. And this mentality, uh, you, you leave the arm, the army with, with this, uh, can do approach.

I can do anything. I have the resources to do that. Um, and we talked about earlier about, um, this ecosystem that is, uh, very, uh, nurturing, uh, uh, all the entrepreneurs are mentoring and investing in, in new entrepreneurs.

Um, and also, uh, everyone, uh, wants to be, uh, the next tweet we talked about that. I think another aspect that is interesting to see, um, uh, also, uh, a rising trend that I, I'd love to, to dig deeper into, is that, um, is the global VC dominance in 2025, we've seen global VCs, uh, investing in cybersecurity in Israel, uh, as soon as seed stages. This is the first year that global VCs are invested more than Israeli VCs, um, in cybersecurity.

Um, uh, so, so the, the majority of the money is global, uh, that entered, that invested in cybersecurity in Israel this year. Um, yeah, No, this is a change. You're right.

Because, you know, originally yo and a handful of Israelis kind of had the inside track on all of these great new, you know, all the people coming out. Like you would think they would camped out in big cars outside the exit to 82. Right.

To 8,200 as they come out. You're writing checks and having them start. But no, every now it's not just the YL and the other Israeli based funds.

Yeah. It's a fundamental change every Global. Yeah.

I, it started, I remember I had a chance to meet the founders of Aramis Amis, um, at an insight partners, uh, uh, uh, insight Ventures mm-hmm. Uh, event in, in Iceland before COVID years ago. And at the time, insight had just bought an Israeli based company to help them do Israeli based cyber well, all Israeli based venture, but they're not even buying the Israeli companies.

Every global VC now has an office in Tel Aviv. Yeah. Or Herz Leah.

Right? Yeah. And, and, and so what did, it makes it a little harder for y doesn't it, a lot more competition.

Mm-hmm. So, so yeah. So, so global VCs have been around, uh, always been around, but they, they, they used to invest in, in cyber in later stages.

Later, Yeah, Later stages. So the, the, the change here that is, they're writing checks now for, uh, two entrepreneurs with a presentation, like the seed stages, our stages. Mm-hmm.

Like the, the expertise of, of wild. Um, I think that it, it, it is, it is an amazing change. And it's, it's, it's great that money keeps, uh, keeps entering here and investing in Israeli cybersecurity entrepreneurs.

And we, this led us to adopt, um, uh, a a split seed model that we've seen, uh, rising in the past couple of years. And I believe it'll keep, keep accelerating, uh, a model where, uh, uh, seed stage cybersecurity com, uh, uh, venture capital such as Wild ventures is co co-investing with, uh, top tier global VCs in seed stage. So the entrepreneurs, the entrepreneurs get like the best of both world.

They get our expertise of the help of we understand the Israeli mentality, and we help them, uh, build their company since day one. And they also get, um, uh, a global, uh, VC invested in C stage that is also also minded for later stages. Um, so they get the best of both world.

And, and we are not, uh, afraid that this will, um, this, this will hurt our investments because, uh, we're experts in building companies, uh, from from day one here in Israel, and entrepreneurs understand our value. So the split seed also, it's an accelerator for them. So we've seen it in the, in the past couple of years.

And, and it'll just keep, keep on growing, I believe. I agree. It also makes for bigger seed rounds, right?

Yeah. I recently interviewed an Israeli company, I'm trying to remember. I don't remember the name, but it was like an 80 something million dollar seed draft or something like that.

Right? It, it's nuts. I mean, Seeds.

Yeah. Some of those seeds Are used to be seeds. Yeah.

They're not three, four, I mean, a good, a seed round, $4 million was a good seed round. Mm-hmm. Right?

Yeah. It kept you a ke it'll fund you for 18 months and, you know, 80 million nuts. Um, but you know what?

So, or there are, there, there's 8,200, there's the Israeli entrepreneurial character in, in, you know, wanting to experiment and, and do things. There's this environment of serial entrepreneurs and second, second growth, third growth companies. Yeah.

But there's something else. And Mitch, I, I'd love to hear you chime in on this, which is, I think what we see, what we saw in 2025 in the Israeli cyber scene is foretelling what we're gonna see in the world cyber scene in 2026 and and beyond, which is for a long time we heard, where's the innovation? Where's the innovation?

Where's what's new in security? Well, we, we're now seeing what's new in security. It's security, having the secure AI generated code, it's security having to defend against AI generated threats.

It's security using ai Yeah. To be more effective security. I think this is going to lead to increased budgets for companies buying security.

It's gonna lead to more security, innovation, and security vendors doing new things. It'll set off more m and a, more liquidity, more investment. Mitch, you speak to a lot of companies.

What do you think I do, and I wanted to share with you, or that, um, we're just getting ready to launch our next update too, our, our buyer decision maker data, and mm-hmm. For the first time, AI is actually one of the things we ask is, uh, what are your plans for investing, either increasing significantly or slightly, or to stay the same, reduce across the number of technologies. AI and development is the top, top of the list, followed by security.

Yeah. Um, security's always up at the top. Um, so for the first time, AI is, AI is kind of in the significant category, so people are ramping up dollars.

So that, that creates a wide open, if not a field that you're already pursuing, of course, whether it's code security or AI agent control planes in the environment mm-hmm. That they work in and security guardrails. You, you have such a even bigger, wide open new field to play in as well as traditional security.

What's your perspective on that? Yeah, so, so, uh, we must talk about ai, right? I, I heard someone says that, uh, this is the greatest, uh, uh, uh, revolution since the, the beginning of, of computers.

Um, it's, it's not a bubble. It's not going anywhere, and it's just, uh, gonna accelerate and, and in our times, first come the technology and then come the security, right? So we're in this, this area where the technology, and then we're building the security on top of it.

So, um, so, so yeah. For sure. So, security for ai, uh, was one of the, uh, of the top, uh, top leading trends, hot, hot spaces in, in cybersecurity in 2025.

Um, um, where, where we've seen, uh, lots of, of new startups, uh, rising. So if in the, the first wave of those security for AI companies, we saw companies like aim, security, our company, uh, prompt security, lasso security, that they, that are secur securing, uh, the use in ai, uh, uh, uh, in corporate, corporate use of ai, if it's, uh, uh, to GPT or, or, or whatever, from prompt injections, from data leakage. Um, basically securing, uh, AI responding to human input.

Now, there is a new wave of security for ai, which is securing, um, uh, the, the, and governing, uh, the, the use of, of AI agents that are operating within your environment. They're, they're practically autonomous employees that are accessing data. They have permissions.

They, they are, um, they have access to assets. They, they do tasks, uh, on behalf of employees. And, and then you need to, a way to find a way to govern it and control it.

Um, yeah, we're moving to a, to an area where, uh, employees are the, uh, the, the tasks of employees are, are AI generated and human led. Uh, and you need to find a way to, to govern it and control it Ing We're kind of creating sort of an open, wide open field of everybody using AI before we've really, truly feel like we've secured it while we're putting the new securities and measures in place that You're talking about. For sure.

Because it, it, it has so many, so many advantages like making, uh, uh, creating super employees, empowering employees, and making work much more efficient. Uh, you can do much more work, uh, in, in the same, in the same resources. And we also see it in, in security, right?

We've talked about, uh, AI enabling, uh, security, and we, we've seen also that in 20, 25 companies that use AI for better security solutions. And we will keep seeing that in the future also. Yeah.

I, I, you know, we're, we're running low on time, but I mean, suffice to say this is a rising tide. Mm-hmm. Mm-hmm.

That's gonna lift all boats, not just the Israeli cyber scene Yeah. But all the cybers. But when you already have that as it's almost a follow on wave to the momentum that's been building Yeah.

In the Israeli cyber scene. It, I think it's going to, I I can't wait to talk about the 2026 report. Yeah, me too.

That'll be interesting. For sure. Yeah, me too.

And, and you can see that, um, that, uh, that the Israeli, uh, cybersecurity ecosystem, we survived pandemic, and we survived war, and we, we survived, uh, internal instability. If I, if I being gentle and we keep seeing, uh, we, we're not just surviving those years, we're accelerating, Thriving, Yeah. Mm-hmm.

Thriving. Yeah. Exactly.

So this give you a sense of, of the cybersecurity, uh, ecosystem mentality. And, and I understand global VC wanting, in wanting to, to get a bite of that. Absolutely.

Yeah. Or, you know, what we didn't mention for people want to download the report at Y Ventures. What's the website?

Uh, yeah. com. Just access it and be easy.

Yeah. Hey, thanks for being on Still Cyber with Mitch and I continued success to you, to yo to the YL team. Uh, we always watch we're fans and you have an invitation for the 2026 report.

Yeah. You'll come on and talk to us. Yeah.

All right. All right. Thank you guys.

It was you. It was great. Thank you.

Thank You. Slo and Ventures Mitchell. Thank you.

Crazy when you think about it, huh? I, oh boy. I just thinking about all the investment conversations we've had with VCs over the years and how much, this is such a huge factor in our market.

And, you know, it was a boutique thing in Boulder, Colorado when we did still, still secure. Yeah. It was, well, Yel was a boutique thing back in 2007.

It was. I, I remember. I remember.

Anyway, hey, I hope you've enjoyed this very, this episode of Still Cyber Mitch, and I'll be back in about a week or so with more guests, more cyber news, Hey, RS a's coming in a couple months. So we'll be ramping up for that. But until then, this is Alan Shimel and Mitch Ashley, and you just listen to Still Cyber.

We're back here with some more, uh, coverage from our AWS reinvent recent, uh, video stand. Uh, if you haven't seen some of our other AWS reinvent, uh, coverage, you know what, at this point, most of the videos are up. You can catch 'em on text, drunk tv, on the text, drunk tv, YouTube channel, or on our Text Drunk TV OTT app.

If you've got Amazon Fire or Roku or Apple tv, or even iOS or Google Play, I, you can get the OTT app there. Um, but let me introduce you to our guest here. His name is Robert Cilla.

Cilla. Cilla. Yes.

Close. Rob, I was close. I left the S out.

Robert Cilla, first of all, Robert, welcome to Text on tv. Thanks you for having me. It's the first time he's been on, so glad to have him on.

Robert, you are with er as, unless you just took the shirt. It is a great shirt. Possible shirt.

It is a great shirt, but I am with sus. Okay. And tell us what, what's your role at suse?

So, I am the Director of Technical and Community Marketing. So I handle our community efforts around, mostly around our consumer community. And we, 'cause we have multiple communities, um, it's like that with any tech company.

So direct to consumer kind of stuff versus, Uh, no, when I say consumer's, people who consume our technology Okay. Is the primary focus. And then our secondary focus is people who contribute.

And on the open side, their focus is slightly different. Where they focus on contributions, less on people adopting, you know, it, they, you know, they kind of build it, it they will come Yeah. Over on that side.

So they cater to making sure the project package maintainers are taken care of. Um, and the needs of these two communities, don't, they overlap, but they're not the exact same. I love it.

You know, we've, over the course of AWS reinvent, I bet you I interviewed a half a dozen to 10 SUSE people. Mm-hmm. Not one of them really spoke about the, they mentioned the community, but they never really spoke about the community.

And so let's start right there if we can. When we talk about the Susa community, and you mentioned there are different facets, aspects of the community, but how do you define this community? Can you give us sizes?

Give us, you know, I don't even know how you would define it. We, I, I define, our community is a large group of practitioners who enjoy the technology, and that is the binding glue that brings them together in our community. Um, to count it, it's hard, um, because you people are in certain channels and they're not in others.

And we estimate anywhere between, you know, 45 to 65,000 people, um, who are active, who, um, they participate in Rancher Academy, which is a LMS platform. We put out, we want people to learn about our projects that, that are out there, or they're in our Slack channel, or they're engaging with us on social media and we understand there's crossover. So that's why it's an estimation.

'cause I don't, we don't track exactly who's who. That's just kind of creepy. We just want you to show up for just, well, But that's, that's part of that open source mantra.

Right. We, we don't track, you know, we're not looking for your blood type or DNA samples like that. We don't wanna know What your kids' names are.

Exactly. We don't Get that. Or even your birthday.

Yeah. But, um, so a lot of it is online, it sounds like. But then like in the event AWS reinvent, are there any kind suse community activities tied to it?

We do a few videos that we post out the community, um, does crossover with AWS slightly, um, when it comes to some of the projects, AWS does have a, a large user community, and there's, there's some crossovers there with that. And we see it more so on the consumer side, very little on the con contribution. Um, for us here, it's just, you know, showing what's the latest and greatest on AWS because we understand that commu there are community users who, you know, they're not customers, but they use our, our projects in AWS and we wanna make sure that we, I don't wanna say meet their needs, but know we acknowledge that that's where they're at.

And the, And they, and they, and they matter. They, they matter. I get that.

What about in-person events in the community? Not just at AWS reinvent, but, So when we have any large event that, that we try to attend, that piggybacks whether what our comm, where our C'S at, whether it's here at Reinvent or Co con or Open Source Summit, we like to engage with our community, let 'em know that we're there. Um, we always have community team members on staff at these events to ensure that, you know, like they can meet the people that they talk to online.

Like these, these are kind of, I don't wanna say they're, they're rock stars in my mind because they're, they're great individuals on our community team, but I wanna make sure that they can connect, you know, in person just 'cause, you know, it's post COVID world, you know, having that interpersonal connection is, is nice sometimes. Sure. Absolutely.

Let me, um, I, I, I, one of the companies I had started was called the DevOps Institute. We sold it about three, four years ago. Mm-hmm.

But we had a, a nice community. It was very simple. It was very easy.

Well, it wasn't that easy, but one, one part of the community, the people who actually had taken our certification classes and our courses mm-hmm. And those, we did know their children's name and their date of birth and all that. 'cause we knew who they were.

They had a, you know, they took classes and they were certified. The bigger part of the community though, were just people who maybe, you know, didn't take a, a real certification class, but somehow consumed our content or, or what have you. And it was always the discussion we always had at the exact level is why would those people want to be in our community?

What would, like, what, what's the advantage of being in a community, if you will? Uh, Well, I, I'd like to, I will speak, I mean, I it in any community, but I wanna speak towards the, the technical community. 'cause you know, it's what we're talking about, and it's fairly relevant, is that individuals have to take some of these skills to work.

And they don't want to know that. They don't want people to know. They don't know.

So being anonymous, being able to go and adopt, learn and grow outside of your normal work environment, to come back in and say, I, I, I don't, I know this so I can talk to it. I'm, I'm participating in it. And I think that's where you see it.

And it does cross over to non, I'm a, I'm a avid cook. I love cooking. I love cutlery.

I'm in, you know, a another community about, you know, cooking and so, you know, new knife skills or something like that. 'cause I want to learn and grow and not think, my wife thinks I don't know what I'm doing in the kitchen. But that's just the same thing.

It's the same adoption that you want to have. And it's not judgmental. Someone comes to the community, they don't know.

It's like, can you point 'em in the right direction? People love to come in and answer questions for them, and they take that back to work, or they take 'em back to school. Absolutely.

So there is the, the, the help you grow, and especially from a work related mm-hmm. Point of view. There, there, look, there are plenty of people who are hobbyists when it, especially things like open source and Linux Yep.

And, and so forth. Um, but it is, it, it, it's a way to advance your personal career path. Let's, let's call it that way.

I, I, you know, what else I, and this is me talking now. I don't have anything to back it up. Sure.

But I think it's part of human nature to, to want to feel part of something, part of a community. And, and as you said, it could be cuddly, it could be cooking, it could be anything. But you always wanna feel like, I'm not the only one who feels this way, who has this problem, who, you know, is working on things, solutions to a particular issue.

I, I think there's, there's something intrinsic to humanity that wants us, that, you know, drives us to be part of community. Yeah. It's a, it's a sense of belonging.

Yeah. So when you, you, you talk to people like we have our regulars in the community, and you talk to 'em, and sometimes they will just wanna say hi. Yeah.

And, you know, and or they will bring you something that they did. And they want, they wanna show it off. And I love that because you're seeing someone who has the same type of passion.

And it, it makes me feel better. 'cause it's not me going, like, I'm just a nerd here. There's, there's other nerds like me out there.

Love it. Look, I built my whole business here on those nerds. Right?

I mean, they're, they're the people who watch our sluff and, and consume this. But it, it's, it's part of being in a tribe. Yeah.

Right? It's tribal at, at its very nitty gritty. It's tribal.

Right. These are people who are in my tribe. It, it, it may not be a tribe that I live with or, or something like that, but we share that common bond, that common interest and, and they become part of your tribe.

And It goes down, it goes even down further where it's like, I, I only like Linux. I don't like Cloud Native. Yeah.

And, and that's okay. And We have a lot of people who are like that. And that's, and it kinda, and you know, there's always rivalries in any type of community, so, you know, we're better than you kind of thing.

Mm-hmm. And it's, I it's akin to sports fans. Right.

And then as a Cleveland Browns fan, you know, I don't really fully understand what it's like from a sports perspective, but I'm sure like Eagles fans or someone else out there, you know, with, you know, a better team behind them would understand that level of, you know, rivalry that you have with the technology. Yeah. My sympathies to you, by the way.

Thank you. Okay. Looks like you're can have a good pick at a quarterback.

Again, though, this I'm, let's not get into football. Let's, I'm a Steelers fan. I'm my own trouble.

But, um, and I, I actually, my, when my brother who's is, he's one of a fire toing guys, and I say, Hey, be careful what you wish were, 'cause look at the Cleveland Browns, right? Mm-hmm. But it's all relative.

But it is, we are, we're tribes. It, football fans are definitely community and tribal. We, We still love we in that crossovers.

We, we each love our teams, the Steelers and Browns. We would, we would love our teams, and we have those rivalries and we can say, oh, we do this better. And you have, we even have it in the Linux communities where, you know, they don't, there's, there's certain schisms that you have and sometimes they get toxic because, you know, we're in an online community.

Right? Yeah. And when you don't have the interpersonal things go get, they get dark, but they usually recover the, and that's what the beauty of a community.

It, it, it like naturally recovers. I I think part of that though is, is, and, and you hit on something when you have a virtual community. Mm-hmm.

You know, it's easy for people to sit behind a computer and say something that they would never say in person. Yep. And it's easy to misinterpret what someone else wrote and may not, they may not be the greatest written communicator, and they, maybe you're taking it the wrong way, or they just wrote it the wrong way.

And, and this, look, I've been in online communities for a long time, maybe 40 years. And, um, well You also, for you, you didn't mention, but you know, we're international. Right?

Right. And you Right. You guys are, And there's, and so there's, there's language things.

There's language I, barriers, but, you know, this is No, no, but there's, there's miscommunication All the time. And sometimes I come into Slack and I'm like, what's going on? Why is there a dumpster fire today?

And I'm like, oh, guys, he missed, he meant this. Right? Like, that's not that word that you think It is, but it doesn't take, It doesn't take long.

Doesn't take much. Nope. It does not.

There's people over the edge. Robert, let me, we're, we're running lower on time, but for people out here who say, you know what? I've been a Souse fan.

I, or I've been a Rancher fan. Mm-hmm. Or both or, or what have you.

I'd like to be more involved in the community. Sure. What's the best on-ramp farm?

io. You can go sign up and you, you get dumped into our general chat and people, and we see, we see people who get put in there and just say hi. And someone from the community team or someone from the community will do, and explore what they have going on in there.

There's, there's a lively chat. Um, there's random stuff that people, you know, post, there's technical checks. So, you know, if they wanna learn more about K three s or rancher specifically, um, those, that's generally the, the best way.

And, you know, I am, I'm in that slack more than our work Slack. So really, that's my world. Well, that is, that is, that's your work.

That's my world. So, um, I come, I go back to work. It's your tribe.

I go, it's yes. And I go back to the work one when I have to, but that's where I, um, you'll catch me, um, is that, that's probably the best way. And again, this is for the consumer side.

When you're getting started in a community, uh, you don't have to come and contribute right away. I always tell people that just come and say hi and, you know, find where you want to connect, you know, and it doesn't have to be contributions right away. It doesn't have to be consuming right away.

It's just showing up and just being, just taking part. Excellent. Is this your last show of the year?

This is my last show. Me too. Um, I'm getting, uh, a very busy with a, and I'm gonna do a shameless plug on Scon coming up April 20th through 23rd in Prague chea.

Um, that's what's consuming most of my time now is the planning for that, um, on the CFP committee. So I'm going through, um, uh, me and a group of individuals at suse going through a ton of talks with a lot of great topics. So if anyone is in Europe can make it.

I do. Well, I hope to see you there. I'm hoping to be there as well.

Okay. I'm thinking maybe I should submit something. Has anyone submitted anything on AI yet?

Oh, I'm kidding. That one right there is, uh, I Think, I think that's the, the vast majority. And I think when I saw, I saw one that wasn't AI related, I was excited.

I was like, Wow, I, I get that way too. It was brave enough to put that one In, put something in, not with It's crazy time to be alive. I know.

It is. Everything's ai. But yes, if anyone can make it, I would love to see you there.

com, find out more information about that. I Love it. Rob, thanks for coming on for helping with us today, man.

This is great. Hey, go check out the rest of our AWS reinvent videos. Scon is coming, I believe it's April 20 to 23rd, as Rob mentioned, in Prague, which is a great city.

You don't have to be in Europe to go to that, though. They do have planes that come from here to there. Yep.

And, and, uh, it might be worth your while. It's, uh, I've done ko actually, the last scon I did was in Orlando near our house. Yep.

But it was a great event as well. So highly, highly recommend it. But that's it for here.

I hope you've enjoyed our AWS Reinvent coverage. This is Alan Shimmel for Techstrong tv. It is always been a challenge for business people to extract insights from business data.

But AI is changing this. Companies like Lytic are making analytics and business intelligence more visible and friendly to people who aren't ready to write database queries or build dashboards. A great dashboard provides continuing value that makes people want to revisit it, and the best are proactive.

Can AI help companies derive real value from their data? That's the topic on this week's episode of utilizing ai. Welcome to utilizing ai, the podcast focused on practical applications of artificial intelligence from the Futurum group.

Each episode brings together diverse perspectives to explore news and use cases in the ways in which AI is transforming enterprise IT and the industries it serves. I'm your host, Stephen Foskett, president of the Tech Field Day Business Unit here at the Futurum Group. Before we dive into today's discussion, let's meet who's on the panel today.

Brad. Hi everyone. I'm Brad Shiman.

I'm the VP and practice lead at futurum for data intelligence, analytics, and infrastructure. And of the three analytics is my favorite. So I'm, I'm quite happy that we're having this discussion today.

And Paul, I'm Paul Blankly. I'm the CTO and one of the founders of Lytics and Lytics. It is an analytics agent that helps answer questions, uh, that people will need to ask in their day to day to make better decisions in their work.

This could be anything from an executive making a decision about, uh, how to better allocate resources, a marketing person allocating ad spend or procurement, making better decisions on, on how they, uh, buy product for a manufacturing company. And as I mentioned, I'm Steven Foskett. I've been hosting the utilizing tech, uh, podcast and utilizing AI podcasts, uh, for, uh, five years now.

And we've watched as AI has grown in usefulness and practical applications, uh, we launched the utilizing AI series with the futurum group analysts last year and all the time, the plan was that we would eventually be inviting on guests to join us in the conversation who are doing interesting and relevant things with ai. I got an a briefing with Lytic right about the time that we were planning this series. And I have to say, it really, um, appealed to me because both of us had the same idea, which is basically, AI is cool, but it's also useful.

So let's talk about how it can be used for practical business use cases. And that's really what Lytic is doing. So before we begin, Paul, let's kind of dive in.

What was the question that was being asked that you decided to apply AI to answer? I think some of the best ones are, are questions that you can't easily answer by yourself. So a good one, that was where I used our own product, uh, to analyze our own users of our product was I had this theory that people were using the product in different ways.

Most of the people chat with the product, but I, I went in and I asked Zoe, our, our agent, that same question. I was like, Hey, can you break out how people use the product based on their usage of different features into different clusters? And then, you know, gimme a sample from each so that I can go have some 15 minute conversations with them and better understand their use cases, what they're trying to solve.

So Zoe went in and helped me, you know, find basically three buckets of people. There's like the people who use, uh, chat the most. They're talking with the AI agent, definitely the pro, like the bulk of our, of our users.

Then there's people who use that and then also use dashboards and other sort of more traditional reporting mechanisms a lot. That also makes sense. Then we had a few people down there who kind of just use the dashboards and like almost never talked to the AI agent.

So I was able to climb these three clusters and then go and have conversations with each of those to better understand their use cases, where we're meeting their needs and what we could do better as a, as a product. So that's an example from my just day to day of how I use, uh, how I use agents to, to better help my analytics needs. Sorry, Brad, I was waiting for you to just dive in.

Uh, we'll, we'll cut Out. Yeah, I, I, I apologize. Dive and Corey.

Yeah. Apologies, man. I, I didn't know if you were doing this more formally, Stephen.

Yeah, No. Yeah, I might have, but I didn't. So you're, I suspected you could get my Way, so, okay.

Let me just start like, I'm, I'm just responding. Yeah, I, I like very much what you're, you're saying, Paul, and, uh, you, I see this in our research, uh, quite frequently that, um, as data professionals work through their day daily tasks, which are many and varied, um, that they are, have found a great utility in using, uh, ai. I, I think initially, um, in the market, especially after we invented Transformers, there was this, uh, sort of idea or a thought that, well, they can't handle structured data, they can't work with a CSV file, they'll just fall over.

Or, you know, we, we can use them, but, um, we can't trust what they say. And I, I find that ironic for a couple of reasons, because, um, in, in my, I'm also a practitioner as well, isn't it an industry analyst. And in my, um, job as a practitioner, I, I find it invaluable for, um, almost daily, I'm, I'm finding new ways to use this, uh, in, in making my job easier.

Whether it's like you're talking about doing some basic segmentation or if it's just data cleaning and prep, uh, or if it's something, you know, more deeper like data mining, like, like you're doing, you know, it, it is tremendously, uh, I I would say useful and trustworthy to a degree. But I, I say it's ironic because when I look at the industry and I look at how, you know, companies are using BI in particular and they're looking at dashboards, I feel like they, uh, have more trust, uh, you know, in, in just their gut instinct or in the dashboards themselves. And they, they put more emphasis on that than they do on, on ai.

So we seem to demand more transparency and accuracy from AI than we do for bi. We kind of say, yeah, it's a black box, but I trust it. What's, what's your, um, experience Paul at, at your, at analytics in terms of how your customers are looking at their dashboards versus ai?

Oh, yeah, I think that's a, that's a really good point about how a lot of the times people trust their gut instead of, you know, what's ever whatever's on their dashboards. I think there's, there's a really good reason for that. Actually, the reason for that is, is maybe best person sonified in, um, in, in a conversation I had with one of our, with one of our pilot customers.

Uh, so I was talking to this, to this woman who's a, who's a PM on, in a major public company, and we were going through, she was asking some questions. The only, we'd only imported a few dataset so far. And she was like, Hey, well I'm, I'm not really getting that much out of this.

Like, what's, what's going on? And I was like, well, you can ask about all the stuff you could ask about on these, you know, that's on these two dashboards. And she was like, well, I don't want that.

It's already on the dashboards. And the, the dashboards don't tell the full story. That's why if you're a PM trying to make a nuanced decision about how people move through your login flow, knowing some basic high level numbers doesn't really give you the information you need, doesn't really answer the question you care about and is therefore just not that relevant for you.

It's maybe useful to monitor, to understand kind of the, the basic parameters of what you're looking at, but it's not gonna actually impact your decision. You need way more sophisticated analysis than you can get out of a, out of a dashboard to actually impact a decision. And that's why for these, these analytics agents, uh, what we're building at lytic to be impactful, they, they've gotta be able to go way beyond what you can do in dashboards.

The PM has to be able to come in and ask really, really nuanced questions, which are not only the valuable questions for him or her, but they're also the ones that are way harder to explain your methodology. We explain what you're doing. Um, and that's what, that's one of the things that the agent has to really excel at to make sure that, that, that that and business person can trust and can actually act on confidently on the data that they got back.

It does seem like people are, are trusting AI already in many cases to give them truthful answers, even as there's this sort of understanding that, uh, generative ai, you know, for example, the search box, you know, Google type generative AI isn't always trustworthy. It seems almost a paradox that people trust AI more than they themselves would say that they trust ai. And at the same time, I definitely feel like people trust AI more than they would trust people.

You know? And, and that's a, you know, even people who would know things, right? I mean, and I wonder if, if, um, you know, kind of looking at my history with, uh, data professionals and how they've interacted with the business, um, to Brad's point, it does seem like sometimes data professionals have labored long and hard to come up with a dashboard or to come up with a metric and, and, and only to have somebody say, well, yeah, no, and, and I wonder is, is is AI going to change that a little bit?

Are people going to trust AI more than a per more than a data pro? I think yeah. They even use dashboards in the future.

Sorry, sorry Paul. But, uh, yeah. Will we even have dashboards?

Are they, are they necessary? Is, you know, are we moving toward an interface that is the human voice and nothing more? And, uh, you know, will we have what a lot of people in the industry would just call headless bi, that's ag agentic that would, you know, find the answer to your question and do, like, Paul, you're talking about with digging deep into the meaning behind the data and the context for that meaning, and putting that into perspective and bringing back like good answers.

I would love that. Yep. I, I actually think there's two different use cases in data that are, that are often conflated, and that's why we get the, like, dashboards are gonna die.

I don't think dashboards are gonna go in anywhere. Um, dashboards solve this monitoring use case, which is like, I need to see the same stuff every week. For me that's like, Hey, what are our usage in the different model providers?

How many people are using claw down versus OpenAI? How many loggings did we have? How is that trending?

Like, which customers are active, which customers decrease their activities? Like that's just monitoring stuff I wanna see every week regardless. Um, but then the, the really valuable use cases usually aren't monitoring.

It's usually a question that you're like, oh, okay, I really need to deeply understand how people are using this. I need to understand where this login flow is breaking. I need to understand, you know, what's going on in this area of the business.

And those are those deep questions that are just not served well by dashboards, and that's what the, what the analytics agents are gonna are gonna take over. Yeah. Do you think, Paul, that, um, through a analytic agents, um, that we can get around, what, what seems to be, to my, to my mind, one of the biggest problems with, uh, dashboarding and traditional bi, and that is utilization across the business and what that means in terms of, you know, how a business actually runs.

We, we've been laboring for decades now, trying to, you know, have data professionals build beautiful dashboards that get used. Uh, but unfortunately, you know, it, it typically ends up where, you know, the analyst spends weeks or longer building a dashboard that nobody uses. Uh, and there's no true understanding of why it isn't getting utilized.

But I, I would love to, to think about, you know, a as you know, an industry watcher, the idea as you just talked about, of being able to balance those two, you know, the two sides of that coin, the, I wanna, you know, just have the same data all the time and I wanna be able to dig into what I want and to have that available to everybody in the business, you know, is that possible? Do you, do you think from, you know, zeny perspective that we can change the business as we've been trying to do for decades now? I think, I think there's, there's two ways to think about that.

It's one, I mean that the, the business teams obviously are not getting what they need out of the, these dashboards, even if it takes a very long time to develop, um, or the dashboards answer a one-time question, which I think is followed most of the pattern where a business person has a need that need is for a specific one time stone, a dashboard gets built, it takes a long time. By that time, it's almost to rear view mirror. It comes in, the person looks at it, they, they understand the one thing they needed to understand, and then they never revisit it again because it was never a recurring mood.

It was never something they needed to monitor in the first place and dashboard just to buy a vehicle to, to, to provide that answer. The, um, the other one though is like, how do you increase utilization? Like, how do you get business people using data more often?

There's certainly the, you make it really easy to ask questions. Anyone can come in and ask an analytics agent a question, get a good answer back, and, and that's a great thing. That's a great utility.

That was, I think, actually only the first step in this because there's only so often you have a question, you think, oh, this is actually something that would be really helpful to have some data to like back up or support my decision here. That that only really crosses your mind, not that often in the workday. So you wouldn't expect a, a massive amount of questions, but are just people coming in down, um, to really solve that.

You need to do what, what the absolute best in, in our industry do, which is you're proactive. You're, you're, you're not just, whenever you're asked a question, you're reactive and you're coming back and giving an answer that's good. Um, you, you need to say, okay, well, if I was a VP over, you know, our, like procurement in a manufacturing organization, what are the things that I would be most concerned about?

How can I proactively go? And before my VP comes to me with questions, I, I come to them and I'm like, Hey, you know, I've, I saw this trend in, you know, these parts suppliers. I know that we have rebates that we can claim on suppliers once we increase X volume.

I found all those suppliers here they are. I've drafted emails even, like, just gimme the, okay. And I can send those for you.

It's like, that's the level of productivity that the absolute best people in organizations have. And I think the agents can absolutely emulate that behavior. And that's, and that's where you get the utilization that's really impactful.

Well, it's not just people coming in and asking the agent questions. The agent needs to be proactive. The agent needs to be able to go to them and say, I thought this would be relevant for you, and it needs to be relevant.

And that's how you build that kind of, uh, continuing value. And you get people to really invest in a tool, I think, is to have them have it be something that is not just, um, not just there for them, but like you said, kind of providing proactive value. It is exciting to think that that is possible in this BI space because again, you know, like we said, BI has always been a very reactive, you know, uh, kind of plotting process where you basically, you know, you're almost requiring someone to know what they want before you build it for them.

And then they, then you go and do it, and then it, you know, they go back and forth and, you know, I mean, Brad, we, we, we experience that sometimes internally with our dashboards. And it's frustrating because, um, what you really want is something that, that just gives you that information. Think about the metaphor, you know, you look at the vehicle dashboard in your car, right?

You know, it's providing you the key information right. When you need it. That's really what we want from our business analytics, right?

Yeah. You want your car to have a dashboard that, that shows the things that are relevant to you at that moment in time. Like your, your left tire has less traction, uh, coming into this turn.

So I'm going to turn on four wheel drive for you so you don't crash. That. That's what we're talking about here.

And we've seen for, you know, quite a few years now, especially after the, uh, chat GPT moment that, um, you know, companies that were building bi tooling were, were trying to do that with SQL text to sql, voice to sql, and with, uh, things like explaining dashboards and, uh, tooling that, that could automate or at least augment some of the workflows that data professionals went through so that they could maybe have more reactive and more immediate, timely access to data. But, you know, I I feel like we're still a long ways away from that overall, uh, as you know, uh, industry just because the inertia that companies have, uh, in, in getting to that and that mindset, uh, is something that I, I think is still gonna take some time to shed, even if we have the tech in hand to do that. Paul, do you see in your customers any, any kind of like, um, do, do they seem like they, they understand and grasp how they can make that leap to that, that real time responsive dashboard for their, for their car?

I think, I think, I think a lot of people do, but it's not, it's not even distributed. It's kind of like the futures here, but it's not even distributed. Uh, what, what we see happen most, which y actually hear it from a lot of other companies that are, that are sort of AI natives like us, is you'll have these power users that just do incredible things.

They're usually the people who are, you know, more, they're interested in ai, they wanna push these tools to their, to their limit. Um, one of these users in, in j Crew, uh, he went and he did a deep dive on trying to be better set up the assortment in our Upper East Side store, some of the most expensive real estate we have in the country. Um, and what he said is, Hey, we've always put stuff, we always put clothes in this store based on historical purchases in this store.

What if instead we looked at the humans who are shopping in this store and picked what they buy through all the channels that we know about all the other stores we shop in everything, and we, we tailor the store for the persona that most often shops there. So we took that approach, which is way more complicated, but with, with Zoey, uh, if he was able to do it and they actually redesigned the Upper East Side store and in, and increased dramatically the amount of children's flows that were there, because that's where they found out that that, that that persona wanted to buy. And that's the kind of thing that you have this power user that just has outsized impact on the organization, um, because of that.

At the same time, you have a lot of other people coming in, getting answers to questions, getting answers to questions like, how many transactions did we have that came in through such and such campaign? And, and those are fine, those aren't bad questions, but those aren't at the same level of impact. So I think the thing that we'll increasingly see as people get comfortable with AI products and, and these, uh, these power users can kind of influence other people in the organization, is that more people feel comfortable coming in and asking those big questions.

Like, try it, try to get it to do something you don't think it can do. Maybe it'll surprise You, right. Break, break it.

Yeah, exactly. And those are the kind of, um, sort of unexpected insights I think that, that companies wish they could get from their data, right? I mean, that's what, that's what they really want.

That's why they've been doing this all this time and trying to build these, you know, data warehouses and building analytics and building dashboards and trying to get business intelligence means it's right there in the name. Uh, but unfortunately, I feel like the whole process has been just so reactive instead of proactive, like you're describing that they just haven't been able to do it. Is that your experience, Brad?

It is, and I, I would say that it, it's, it's funny because, uh, when you talk to data professionals, uh, and across the spectrum, so every, everyone from a casual business user that's using data to the, the person that's in charge of maintaining, you know, realtime data pipelines, um, or, or the data scientists working with the data, um, you know, in, in various select deep ways, uh, and all of them have, like, you know, said, you know, we are shifting toward the business. We wanna be able to focus less on the syntax and more on, you know, the intent. And one of our, one of our, um, uh, we, we do our yearly prognostications and one of mine this year for this re this area is the rise of the AI Shepherd.

I'm, I'm calling them. And it's, it's basically to say that, you know, we, we've tried augmentation. That's old news, new interfaces, natural language.

Uh, people don't want to write SQL to, to get something done. They want to just state their intent. And how you do that, whether it's in an interactive dashboard that has Zoe, let's say, as your co-pilot to work with you on that, or whether that is just in a chat interface or whether that's in a line of business app, uh, that you have, you know, your traditional pull downs for what you're working on for that workflow is irrelevant.

They, they want to just be that, they want to be the person that has AI with them to, to make these decisions, to bring back these insights. So we're seeing, you know, the traditional data, uh, professionals shifting toward this. I'm not a technician anymore.

I, I'm more of the validator, curator, adjudicator, uh, facilitator to, to, you know, innovation built on top of data. So they want it, they, they really, you know, the data professionals really want it. The business users, I think, you know, need to, to sort of see that.

And as Paul you mentioned, you know, if you have people in the organization that can trumpet that and, and promote that as, yes, this is here today, we can do this today, that that's what we really need for everyone in the indu in the organization to be able to say, you know what? I don't have to wait two weeks for somebody working in SPSS to build a dashboard for me. I could get, I get an answer like right now.

Totally. I think the, I think your, your way of framing it as, as AI shepherds is really good, because when you think about what are the barriers to, to these agents actually working inside of a complicated enterprise, there's like two facets of it. There's context and there's sort of like explainability.

It's like, do I know what you did? Um, the context part is straightforward, but still complicated, which is there's a lot of historical patterns you have. There's a lot of facet knowledge hidden in dashboards, hidden in databases, hidden in the, just the head of, of the data, people who have been having to answer these questions and accommodate all the weirdness in their data.

Uh, because everybody's data is weird to some extent. And, and getting, getting all of that information and making it really easy for, as you use the product and as you get value to add that context in as you go, instead of having to kind of put it all together and boil the ocean before you can start asking any questions. So, so that's absolutely key.

That's like gathering the context. The other one is the explainability, and well, like, why do I say explainability instead of trust? Because any really good analyst, the really elite analysts are gonna come back and not just explain to you like, Hey, I got this such and such number.

They're gonna say, Hey, I follow, this is my methodology. Like this is, this is what I followed to get to this. And they're gonna actually show their work.

And what that does is, instead of the VP or whoever coming back and being like, that number's wrong, obviously, like, um, have you guys even looked at this before? Um, they're, they're gonna say, oh, okay, I see you followed this methodology when I wanted you to do this, but I didn't actually say that you should do this other approach instead. And that's the same way that an AI agent builds.

The, the trust is through that explainability and understanding where that end business person can understand, Hey, this is the approach you took. Great. That's what I wanted.

Or actually I wanted to see it a different way. I wanted you to approach this differently. And, and those are the two sort of fundamental things.

It's like that context of like, what's going on in the business, how do I answer questions correctly for this business? And then the showing your work, the, like, how did the end user know what I did and can be confident in the, the end result? You know, what AI is really good at right now, when you, when you look at, um, areas like, uh, software development in particular is in documenting, um, that methodology.

Um, and in turning it, we, we've had some tooling now that just has swarms of sub subagents that all will go toward tackling a, a given problem. And they'll come up with a plan called a spec, spec driven development. And I think that we should start seeing if we're not already the data professionals picking up that same methodology for how they do it.

Because AI is terrific at building that, that taking that knowledge that usually just sits in somebody's head and operationalizing it. Yeah. You know, that's, that's a really good point.

And I think that that's maybe something that we can kind of step back from the specific conversation about business intelligence and, and, and talking to the folks who are listening to this, who are not maybe in this field, but are wondering, you know, what, what, what could their takeaway be? The idea that AI can help them, um, I guess understand the whole process, you know, talk to us a little bit more about that, Paul. Yeah, I think that's, I think that's maybe the most important aspect because what you, what you want is you want a virtuous loop where the person can ask a question, get an answer, they really understand how the AI went about getting that answer.

Then they're more equipped to ask a better follow up question. They're more equipped the next time they have a question. They're like, I actually know a bit about how this, this works now.

And then they're, they're able to ask better and better questions as you go. And you get this virtuous cycle where you ask a question, you learn a little bit more about how this is structured, you get the answer you need, then you can ask better questions as you go. And that you get this virtuous cycle where people are asking better questions, getting better answers that are more relevant to them and all because they actually understand what approach to AI has taken.

And that's the, that's the just so crucially important. Yeah, I, I'd love that because, um, as we were just talking about with, with documenting all of that institutional knowledge and not losing out on, on tribal knowledge, um, is one of the biggest challenges that companies face. And if you can introduce a technology, whatever kind of technology that preserves those and, and honors them and puts them to work in improving that cycle of question and answer, uh, whatever domain you're working in, whether it's bi or, you know, sales enablement or, or, you know, any particular area in the business that, you know, an investment in that is an investment in the future of the company.

'cause as we all know, um, jobs are changing, roles are changing, but the business itself is, is changing. And so we need to, as an industry, invest in the technologies that can, you know, take the concept of this business, everything from the semantic layer up to the, you know, business decisions and the data points that sit on that interactive dashboard. And to make that more resilient and more responsive to, uh, an ever changing environments that we all live in right now.

That's what we need. Yeah. And the real, the really important part there is, it's gotta be really easy as you go, as you're asking questions, the agent is remembering things.

You are able to say, Hey, great. That's that concept. Remember that now it needs to be really, really easy as you're going.

It can't be like a big, you know, months long project. Like, set something up before you start using it. You've gotta dive in and start using it now and have it learn with you as you go.

That's the, that's the pattern. Yeah. It's called Forward slash memory as you're, as you're typing.

And, uh, they could tell it to remember anything you want. Well, you know, it's funny that, um, you know, the most effective, um, you know, AI power users are generative AI chat chat power users that I've talked to you. The, the way they do it is kind of flipping it on its head and having the, um, having it interview you instead of you interviewing it.

So instead of saying like, Hey, give me an answer, you say, Hey, um, if I wanted to achieve an answer, what were the, what are the questions that you, you know, I should be asking? What are the facts I should be bringing forward? Um, how should I be thinking about this?

And it helps you to organize your own thoughts and your own queries in a way that can help then the AI helping you. And, and I guess Paul, that's, that's the kind of thing you're talking about, right? That, that, that the more questions, the more interaction you have, the better it gets instead of the worse.

Yeah. Yeah. Yeah.

It's, it's gotta improve. And then I think, like you said, the other, the other really component, the, the really important component there is asking the right questions and asking the right questions means, just like you said, you're not asking for a specific data point. You can do that and it'll give you an answer, but you're telling it the problem you wanna solve instead.

Yeah. Because almost inevitably, when you do, it'll, it'll pick out that data point you had in mind for that problem. That'll, it might also add another one that is really relevant that you just didn't think about.

Humans are bad databases and the language models are actually pretty good databases, so much better than humans. So ask them the, ask them your goal question, ask them what you're going for, and they'll probably catch something that you just didn't think of in the, in the moment. It's a really helpful pattern.

Yeah. I like to have my agents, um, use the Socratic method to, to argue a point. Well, on that note, um, perhaps then, shall we continue the No, I, I, I, I'm not even gonna try.

I'm not even gonna play that game. That Was cute. Yeah.

So this, this has been a really interesting conversation, and I really appreciate the fact that we were able to, you know, kind of go from specific to general here, and that we were able to come up with some really interesting ideas for how people can make best use of this technology. Um, before we go though, I do wanna give you a chance, uh, Paul, uh, tell us a little bit more about Lytic and, and where people can connect with you and find you and learn more. Yep.

You can find me on LinkedIn. com. If anything that I've talked about is interesting, please, you know, chat with us like a demo.

Um, I'll also be talking at day-to-day Texas in a couple weeks, so if you're there, gimme a pen. I'd love to, love to chat, uh, while we're out there in Austin together. Great.

Um, Austin, hey, that's where RUM is. Uh, Brad, how about yourself? I know you're not in Austin, but, uh, where are you gonna be lately?

Uh, I'm, I'm actually home for a couple of weeks, which is, which is nice. Um, and I'll be working on a couple of, um, comparative reports that are themselves using generative AI for, uh, a project that we have internally, uh, here that, uh, we call Signal for Signal Reports. And one of those that I'll be working on is around semantic bi tooling.

And, uh, so analytics will be, will be featuring in that as well as many others, um, because this is a rich, rich marketplace with a lot of great people working on, on this solution we've been talk, talking about today. So I'm, uh, I'm looking forward to, to getting that going. Yeah.

And if, uh, people wanna see that report, uh, Brad, where can they find that? com. Uh, and they can find me on LinkedIn all the time at Brad Shiman.

All one word. Excellent. Well, thanks so much for this, and, uh, thank you everyone for listening.

I hope you found some, uh, interesting ideas here for your own use of ai, your own practical utilization of ai. Thank you for listening to the utilizing AI podcast this week and every week. If you enjoyed the discussion, please do subscribe.

Uh, you'll find us on YouTube as well as in your favorite podcast application. And of course, a rating and a review would be helpful. This podcast is brought to you by the analysts and experts from the RUM Group, where insights meet ai.

For show notes and more episodes, head over to Text Strong ai, the utilizing AI YouTube channel, or the text TV app. Thanks for listening, and we will catch you next Wednesday. Hey, everyone, welcome back here to our continuing coverage of AWS Re Invent.

You know, we don't do every video interview live at reinvent because there's embargoes, there's other considerations. And so this is one of the videos we recorded at, uh, reinvent in Las Vegas, and we're bringing to you now, just a few days later. I want to introduce you to my friend, Dore Laur.

Dore is, uh, the CEO, I think founder of cid. Yeah, Yeah. Co-founder, Co-founder of, of CID db.

I Got help. We all need help. Do's been on with me on Textron TV for years and years, but it, it's not often I get to see him.

He's, of course, in Israel. Uh, we were supposed to be in Israel right now, but we're not, uh, for Cyber Week, and it just didn't come together enough. But do's great to see you here in person.

It's great to have you. Thanks. Thanks for hosting me.

It's a pleasure. So, let, let's start with this, though. Not everyone has seen you on text Drug tv.

We, you know, we're not, let's face it, we're not CNN or any of those, but yet, give people a little bit of your journey to, to founding, uh, Sila. Sure. Um, so I'm a technical founder.

Uh, I have roots in computer science, and, uh, initially in my career, I went to work for a terabit router company That early days tried to take over Cisco's core business in, in 2000, uh, the bubble burst, so it didn't work that much, but we did have a fabulous product and a drop in replacement for Cisco CLI, I'll, I'll come later on with more of the importance of, uh, drop in replacements in products. Mm-hmm. Um, and later on I did something with Blade Centers, and then I joined the company, a startup company, where I met my existing co-founder ti and my, uh, existing, uh, chairman who was, uh, the CEO back then.

Uh, that setup had had to pivot three times. This is where I learned how to pivot uhhuh. The last pivot, we came up with the KVM hypervisor.

So to, uh, renovate around the new hypervisor, a new approach that, that was the KVM, it worked really well, and Red Hat acquired the company. We, uh, spent their four years, uh, improving KVM and also the Linux Colonel, and I'm a big fan of it. And, uh, afterwards, we wanted always to have our own startup.

So we, we left Red out and opened this company. Uh, originally, uh, it wasn't around databases because we had a lots of, uh, virtualization experience, so we mm-hmm. We started with, uh, an operating system that should have bit, uh, bid Linux in, in, uh, virtualized workloads.

Uh, the OS exists, uh, still today. And I met a customer yesterday who runs Sila and knows us because of that s uh, 'cause of that os Really? Yeah.

If you don't mind, what os was this? It's Called, uh, OS v, it's, it's a unikernel. Oh, Okay.

Sure. Um, They had their moment in the sun. Yeah.

Uh, the Docker kind of sucked all of the air from the room when we around when we launched, but, uh, this is where we, we were familiar with other databases. We, we want to show, uh, the gains when other databases run on top of r os to be faster than Linux. And we managed to accelerate Redis by 70% because we loaded the application into the kernel space was faster.

When we did the same with Cassandra, the performance didn't change much. Really. We realized that the overhead of Cassandra, uh, is itself and, and not, and if you replace it with a fast os it, it doesn't change it.

Uh, so we said, oh, that's can be a good idea for a pivot, because we didn't get enough traction. And with why, once we rewrite Cassandra from scratch, keeping the compatibility like the Cisco days, uh, also like the KVM days, it's, it's also about compatibility, uh, with, with other things. Um, and we re rewrote Cassandra from scratch.

That's what Sila DB does. Uh, it's also, uh, nowadays compatible with Dynamo db. It's a drop in replacement, and it's a standalone database that can run the biggest, most scalable workloads in the world.

I love it. What a great story. Huh.

And it's also, uh, you know, for, for geeks, right? You're, you're, you're a geek person. I'm a geek person.

A lot of the people out here are, we do this. I mean, it's nice to be able to make a living doing it, but we'd also do it because we love Yeah. Playing with this stuff.

And, and this is a great story where your passion led you to, to doing this. Um, it's been now how long with s it's kind of six years, seven years, eight years, how long? Mm-hmm.

Uh, now it's, uh, it's more than 10 years. 10, yeah. Even, uh, our 11th year.

Really yeah's, you know, what that, and that's something also, quite frankly, to be proud of, right? Mm-hmm. Because what do they say the average company, if you make it past three years mm-hmm.

It's a big accomplishment. So it, it's, it's all obviously here. Um, now talk to me a little bit about how people engage with Cilla, right?

There's open source parts of it, there's commercial parts of it for people out there saying, you know, we're always looking for better performance, better bang for the buck. What, how, how do they kind of jump into Cilla? Um, so, uh, we started, we were big open source fans.

Uh, we, we started with open Source, actually, uh, a year ago. We changed the license, I remember to source available mm-hmm. At the time, a year ago.

I, I was just sitting here. Um, so it's source available. We do have projects which are, uh, open source, like our, What even source available.

Let me ask you a question. In the year you did that, how many people have asked for the source? Um, so PE people do appreciate the, That it's available, The source, But it, it, this is, but this is something, look, I've been an open source too for 25 years.

The fact of the matter is, 99% of the people never look at the source code or make a change to it. Not, maybe not. 99, 90 8% of the people never look at the source code, never make a change, you know?

And, and so what they really want is free, Uh, yeah. People like free. And, and we, we have, uh, a freemium offering right now.

We're, uh, now it's source available. It's allows us to, uh, allow people to look at the source and, and also have the, uh, comfortability that the source is, is available for virus cases, uh, for future con continuity. Uh, but, and we have some control to say, okay, up to this, uh, level, it's free and beyond that level, you need to pay because we are here 11 years on the road.

And, and it's a business, right? Someone's gotta keep the lights on. I, I agree with you, But I, I, I do understand people, uh, who are passionate about, uh, the source code.

And there's a lots of, uh, small things and small changes where things matter. And, and we have, uh, open source, like, like our core engine, it's called csar. Uh, it is open source and it's license, it is not a GPL, uh, it's license is, uh, uh, Apache because it's important for, for people to use it within their products.

And that's why we haven't selected, there's a ton of No, Absolutely. Changes. You know, one of the nice things that I've seen happen in the open source community over the, as I said, 20, 25 years I'm involved, is that most users recognize that though, open source may be free, someone's working on this.

Mm-hmm. Someone's entitled to get paid for their time and their effort and everything else. They may, they may quibble with how much mm-hmm.

But you, you know, it, it's ludicrous to think that people are gonna volunteer this outta the pure love and, and not make a living, you know, not be compensated for it. So I think that's been a positive development overall in the open source space. Mm-hmm.

Right. It used to be, oh, you know, you're looking, you're in it for the money. Everyone's in it for the money.

We have to keep the lights on, we've gotta feed our families. But, you know, it's just, it's a fact of life. I mean, and if you don't wanna recognize that because you're some sort of, you know, like open source zealot mm-hmm.

Frees in free and frees in beer, don't use the product. What can I tell you? And, uh, having, uh, paying users allow us to invest back in the product product, Absolutely.

It makes the product better, Product better. Um, so that's primarily what we do. And It's a flywheel As a, as a vendor that, uh, used to, uh, release both open source releases and also, uh, gated product releases.

You double the amount of releases. I was Just gonna say, what a pain in the Yeah. You know what that is A hundred percent.

I, I agree with you. So there, but there is a freemium version. You can go check it out, play with it.

If you do wanna look at source code, and that's your thing, it's available to you as well. Um, Dora, let's talk reinvent here. You guys are here.

It's been an interesting kinda reinvent because, you know, we, when I, I just finished writing an article when I first got here Monday, and I looked at the keynote, you know, agendas and everything. They gave us a press preview. It was obvious, it was all agenda AI all the time, right?

It was all about ai. But over the course of two, three days that I spoke to people and saw things and walked around, see a lot of news about DevOps, cloud native platform, engineering databases, hardware, hardware's, AI stuff too, but hardware, um, you know, it, I maybe didn't hear as much as we normally hear about, like things like S3 or serverless or Lambda or these kinds of things. But the geeks are still here.

The developers are still here. The ops, the DevOps folks are still here, enforce, what have you seen? Um, so AWS is, uh, a giant, yeah.

E even more more than that. Um, and nowadays they do innovation across, uh, across the year, not just them, also their competition. They, they have to, um, so our announcement, I think that they're not holding the announcement just for, uh, this event, uh, recently they released a new GRAVITON instances.

Yeah. Graviton five is coming. Yeah.

And, and then, and the, and the GRA Graviton four was released. Right. And, uh, we are, we measured graviton four with cila db and, uh, it, it offer fantastic, uh, performance and that translate to better TCO.

So for us, it, it's super, that's exactly what we need. Um, so the, there's a lot of, uh, gradual improvements always on all of these products. Yeah.

Um, so it's for, for, uh, for, for, I'm, I'm pleased for that. It's, it's good enough for us. What about, now I know you're exhibiting, what about like, you know, traffic at the booth, conversations with people?

What are you hearing? Uh, well, the, there's, uh, no shortage of, uh, of traffic at the booth or traffic, uh, here in Vegas. Uh, regarding, um, the entire AWS and, and the ecosystem, uh, it, it's mostly about, about ai.

Like, uh, yeah. Uh, we, we see that a surge in AI use cases. Uh, now about half of the use cases are, uh, directly related to AI In silla.

Uh, in Silla. Yeah. In, in.

So Explain that to me. What, what's the use case there? Um, we can pl split it to, uh, three categories.

Uh, one category is the, that we're part of the AI stack. And, and during the, uh, training and also the, uh, serving processes, uh, the, the stack need to just access a tone of objects and, uh, need the fast database for it. It's part of the AI stack without doing anything, uh, special for it.

Like, uh, uh, distributed databases is in demand for high workloads. And, and those are high, very high workloads. Sure.

And, and can be, uh, part of the big LLM companies, or it can be a smaller, much smaller company that started start their AR journey. That's number one. Number two is a feature store.

Feature store is more of a machine learning, but it's, it's part of AI still. And, uh, feature store allows people to classify, uh, users or, or sometimes agents, uh, automatically. So it can provide recommendations for, uh, e-commerce, for, uh, fraud cases in variety of other cases.

And we we're big in, uh, feature store case and feature store needs, uh, a fast database too, to quickly come up with, uh, to, uh, classification that, uh, you as a user was selected and, and what's appropriate for you as a user either to watch on TV or to get an ad, et cetera. Uh, I love it. This is the second one.

And the third one is, uh, a vector search, um, to, to do LLM on your private data set set. Uh, that's why, uh, the, the, this whole category of, uh, a rag Right. Was rag with vector database.

Exactly. So, uh, we added, uh, a vector search, uh, ourselves. And we, we already have a, a beta that receives lots of interest.

And, uh, we, we are going through this month in December, uh, go live with the general availability of our, uh, rag, eh, vector search store. Really? Yeah.

That's f that. So in essence, they could use Stiller as their vector database then. Mm-hmm.

They're creating small language models or, or Yeah. The rag stuff that's gotta be big. No, Yeah.

That's, uh, fantastic. Our, uh, eh, vector search is the most scalable. We can easily run a model with a billion, uh, objects.

Uh, very few, uh, vendors can even get to a billion. And we can do that with hundreds of thousands of requests per second. So we, we scale, uh, to, to very high numbers.

And if, uh, people have, uh, lower or medium demand too, like, uh, most will have a model of, uh, 10 million or a hundred million objects, then we can give, uh, the best latency and, and also very low price point. That's fantastic. Look, there's a lot of people saying that we've scraped all there is to scrape for these LLMs and that, you know, get, making generative AI or even agen AI better by increasing the LLM and the data we have to train is, is diminishing returns.

And that the way to go is maybe SLMs more rag, you know, uh, well, there's some people who say, we need to go away from LLMs all together and go to this world model and stuff like that. Mm-hmm. Um, but certainly, I, I believe there's gonna be a lot of activity in, in the SLM rag kind of space.

And, and not only that, because as we develop AI for specific use cases, I don't need the whole world of the internet. I just need, especially if it's my own proprietary information. Right.

And I don't wanna put that out up there. I want it right here. Just, and so I, I think that's a huge business for you guys.

Yeah. Congratulations. Thanks.

Uh, it's, it's, uh, the, the market demand. Yeah. It's, Yeah.

Well, no, this, That is, it's not just an opportunity. It's also a defensive move. Because if we won't do it, then uh, customers will go elsewhere.

Uh, to, to be frank, and yeah, the, the fact that, uh, people would expect, uh, all of the ease of use of LLM on the public data set on the internet, they expect to have the same when they come to every vendor. And to ask, I free text search, uh, your questions in, in one liner, and get immediately the best results without diving into a very complicated ui, that's a power of LLM. And sometimes it won't be people, but it be agents, right.

Uh, that come and, and automated and get the queries automated. So that begs the question, is there a an MCP server in your future, Uh, in the future? Absolutely.

Yes. All right. Hey, let's fast forward past AWS for a second.

People are watching this after the, after the show. Anyway. You guys have some new announcements that you're previewing here.

Mm-hmm. Share, if you don't mind a little bit. Thank you, uh, for the opportunity.

So, um, uh, we'll also move, uh, from beta to general availability. Our X cloud a, a, a managed platform. Uh, X Cloud is, is, uh, the new generation of our core database with database as a service management consumption.

The unique thing about it is our new core architecture, which is called tablets. It's way, way more elastic than any other database or even infrastructure in the industry. Uh, we, we were okay with regard to, uh, the speed of, uh, increasing the cluster, scaling out, and then scaling in.

We were, before this technology were, we were okay, like, like an average vendor, but there was a demand to do it much faster. And frankly, we also compete with DynamoDB. We're drop in replacement and DynamoDB, uh, was the first NoSQL database.

And up to this change was the, the best in the industry. You can easily scale up and down, uh, very easily. And, and if your workload changes throughout the day, uh, then, then you can, uh, instead of paying for the peak consumption all the time, you can just have the workload follow, uh, uh, the work, the workload should follow the usage, right?

Dynamically. So that's exactly what, uh, X cloud is. Uh, we, we have, uh, the technology based on components called tablets.

We break the gigantic database of, uh, a petabyte of data to five gigabytes chunks. Right. And we can move them around super quickly.

Uh, we, we can also even, uh, it allows us, uh, both to scale super fast. We, we can increase capacity, quadruple it in 10 minutes. Mm-hmm.

So you can go from, uh, 500 K to 2 million operation per second in 10 minutes, But could you go back to 500 K and 10 more? And that's right. So, Because sometimes with these things, it's like blowing up a balloon.

Mm-hmm. You know what I mean? It never goes back to the size it was before you blew it up.

So we, we can, it, it's not, it, it's, it's, um, indeed complicated. Yeah. But we can also go back and, and shrink and, and that's the user workload that, uh, goes, comes and goes, whether it's a Black Friday or, or on a daily manner.

Uh, so, so that, that's a big improvement. Uh, and, and big TCO improvements and, and usability improvement. Sure.

Uh, also, it's, it's, it's pretty unique. Uh, we have a child per quart, uh, engine. So let's say if you have, uh, a machine with, uh, 32 cores, we, we'll have 32 independent threads in the server.

Wow. Uh, if you have a 64 machine, then we, we will have 64 threads, uh, in, in engines within that machine, and it'll perform twice as good to 32. Now, let's say if you have a 64 way machine, uh, but actually you need, uh, um, 66, uh, threads and you have 64.

And now would, would you buy another machine for 64? It's, it's expensive, right? So instead we, we can mix and match and we can have 1 64 machine together with, uh, a tiny two VCP machine next to each other because of the flexibility and the hard.

So it's Real Distribution and the starting, we, we can combine the two. Haven't seen any other vendor can do that. No.

And what the user receive is efficiency. Uh, they have exactly what they need. They don't need to buy excessive large servers, which are expensive on AWS, uh, They're expensive everywhere.

It's not just AWS but really what we're talking about here is almost like a finops play, right. Because that's, I think that's where we are, especially in cloud usage, right? Look, we're talking about spending $5 trillion on data center AI factories, but the fact of the matter is, when I talk to people, they say, I wanna get control of my cloud bill.

Hmm. I wanna redu, I wanna be more efficient in my use of these resources. And, and that's why I made the joke with the balloon blowing up.

That's pretty much how the cloud is, right? It never seems to go back down. People, they want that ability to have insight to turn that dial, and they want the ability to say, how can I do this more efficiently?

Mm-hmm. Yep. And, uh, our customer success team works with customers.

And if we both see, let's say you sometimes utilization people can check their database, how much it, it's loaded on an average basis. Most databases are, are not that loaded. Uh, on, on a, when I'm not talking about the spike, I'm talking about normal, uh, day usage overnight, it can be 10%, uh, or 20% utilize and you pay for the entire thing.

But that was always the pro, that was the promise of the cloud. That elasticity was a up and down thing. Yeah.

It wound up being more of an up thing all the time. But it's good to know that's there. So this available, well, by the time people are reading this, it'll, or excuse me, by the time people see this, it'll be available.

It, it's, uh, today, uh, a avail dated to, uh, AWS conference available as beta and, uh, the time people see it available as general availability. Excellent. Good stuff.

What else from, Um, so it's mostly this. We, we do have, uh, lots of, uh, things that we develop like tiered storage mm-hmm. Uh, in, in other technology to, uh, reduce the bill.

Uh, normally we use NVME for fast source fast performance, and it's also relatively cheap compared to different alternatives of, uh, of storage. But, uh, SS three is cheaper. The problem with S3 is that latency is prohibitive, heavy, big.

It's a 50 millisecond, 100 milliseconds. Uh, and with third storage, uh, we can keep the whole data on fast and VME and automatically move the cold data to S3 and come, come up with, uh, a good solution. 'cause sometimes you keep, let's say 30 days of, uh, of history on, on, on Sila in the NVME, but you'd like to keep one year of data and, and access it through the same API and not develop a new access for it.

So this allows users to, uh, have one API and, uh, a very cost effective solution. I love it. Good stuff.

You know what, we didn't, we didn't even mention the website, URL for people. Want to go find all this out on their own. Dig in a little deeper.

What's the, what's the best URL to go to do? Thanks. com.

com. Just as it says underneath his in his lower third. All right, Dora, it was a pleasure seeing you.

Safe travels back home. We are wrapping up now again, you, you're seeing this after we were here at, uh, AWS Reinvent, but it's part of our A AWS reinvent coverage. And if you need to find this back on, it'll be listed under the event coverage.

But for now, this is Alan Shimel for Text on tv. Thanks for joining.