The Enterprise AI Cloud Platform Powered by Nutanix Unified Storage
At AI Field Day 7, Alex Almeida from Nutanix presented the company’s vision for enabling enterprise AI initiatives through a robust, cloud-native infrastructure built on Nutanix Unified Storage. He began by highlighting a critical industry insight: while interest in AI is surging, a reported 95% of enterprise generative AI pilots are failing to reach production. This widespread issue, he explained, is not due to deficiencies in the AI applications themselves but rather due to the lack of a strong, scalable data infrastructure that can support AI at the enterprise level. As companies attempt to scale pilots into production, the complexity of integrating data from edge, core, and cloud environments—along with difficulties in orchestrating networking, compute, and storage—presents a considerable barrier to adoption.
To address this challenge, Nutanix is focused on delivering a seamless platform that simplifies the infrastructure required for AI. Their solution is the Nutanix Cloud Platform, built on a modern server-based architecture with a focus on scalability, manageability, and consistency across compute, networking, and especially storage. This shift from traditional three-tier architectures to cloud-native technologies supports containerized applications and Kubernetes workflows. Nutanix sees its evolution from hyper-converged infrastructure (HCI) into a robust cloud-native platform as a foundational change that sets the stage for the next decade of enterprise computing, particularly for AI and PaaS environments. With components like Nutanix Kubernetes Platform (NKP) and Nutanix Cloud Clusters, organizations can run applications consistently across on-prem, cloud, and edge environments.
A central piece of this AI-ready infrastructure is Nutanix’s Unified Storage offering, which provides file, block, and object storage all integrated into a single platform. Almeida emphasized their data management capabilities through Nutanix Data Lens, which adds analytics and cybersecurity features such as ransomware detection. He also pointed to Nutanix’s strategic partnership with NVIDIA, underscoring their certified support for NVIDIA’s GPU Direct Storage and active involvement in NVIDIA’s Enterprise AI Factory. These collaborations ensure that Nutanix’s solutions are aligned with the latest AI data platform innovations. Overall, Nutanix aims to empower enterprises to overcome infrastructure hurdles and realize real ROI from their AI initiatives by providing a modern, unified data foundation.
Recorded live in Santa Clara, California on October 30, 2025 as part of AI Field Day 7. Watch the entire presentation at https://techfieldday.com/appearance/nutanix-presents-at-ai-field-day-7/ or visit https://TechFieldDay.com/event/aifd7/ or https://www.Nutanix.com/enterprise-ai/ for more information.
Transcript
So we have a lot of interesting things to talk. So strap in, right? Um, the key here that we want to talk about myself, I'm the senior product marketing manager, uh, with Nutanix for Nutanix Unified Storage, and I'm joined by Manoj Vishal and Mike, who will walk you through a lot of good technical, interesting detail on, on our platform and the solutions we have today.
So I wanna set the stage a little bit, right? When we talk about AI and, and all the hype that's around it, how many of you have seen this report out there, right? That, that everybody's talking about an MIT report.
95% of generative AI pilots are claiming to be failing at companies, right? Based on this report. And the reason is, well, let's look into a little bit deeper.
And this report did that on why, what's stopping these organizations from making progress and seeing ROI in this? Well, it's not the ai the AI applications are, are smart. We all play with chat GPT and Gemini, and it does really cool things.
What it is, is it's the lack of a strong data foundation. And what do we mean by that? Well, when you look at taking an enterprise AI pilot live and scaling it up, it's all well and good in your own little sandbox and pilots and people can, you know, we had Rogue it, now we have rogue AI where they go off into a cloud instance and implement a small, um, instance of, of the AI application.
Everything works great. Now you start pulling in all the enterprise data to start going live and scale. And there is many moving parts as you can see here as we're showing, right?
So Edge, core and cloud, you have data all over the place that data could potentially, uh, add value into that AI workflow, right? And that pipeline, there's also networking, there's compute storage itself and the management of that, right? As we, we were alluding to.
And then on top of that, it's setting up the AI application. So as an application owner, you're relying on all of this underlying plumbing to do what your application wants it to do, right? And that's very difficult when you go to scale.
So what is it that we at Nutanix are looking at A way to address this is it's trying to make this infrastructure as seamless as possible. And the idea is that is the, the orchestration of this needs a platform and it needs a consistent platform, not only for the compute and the networking, but also a good data foundation, as I said, with a storage data platform that allows you to do management. So the base for everything that we're gonna talk about today with you and dig deeper into is the Nutanix Cloud platform.
And that foundation has been set to really drive the mission of any app, any data, and run that anywhere, right? Whether It's on-prem, in the cloud or at the edge. And so when we talk at things about AI factories and now see the realization and make it possible, right?
So we'll, we'll get into this in into more depth obviously as we go along, but just kind of why are we here, right? Let's take a little bit of a, a history step, right? From a Nutanix perspective and from an industry standpoint.
We all remember all the way from mainframe until VMs, the three tier architecture rule of the day. Now we're looking at cloud native applications and this infrastructure no longer suffices. So what we think about and we look to is now a server based architecture where we scale up and add nodes and and grow that way.
And these applications now have a a a A home where we can now run containers and do cloud native workflows. And this is really the future as we see things. So from a Nutanix perspective, you are probably well versed in our, our foundation in our history.
And that HCI was the beginnings. Um, and we've done a lot of good innovation in those first 10 years around HCI. When we look at the last five years now, we start thinking about cloud and things like NKP and Nutanix Cloud clusters where we start relying and putting in the foundations for that Kubernetes workflow, that cloud native application optimization.
And so the thing is, where do we see ourselves in the next 10 years? And where we are now is in this cloud native pass and AI world. It's that we have a platform with NKP and all of the architectural, um, innovation that we've done over the years that really provides the solid foundation for this next wave and this shift that we're seeing.
And so we're here to talk about AI today. This is the actual platform, and we'll go into and explain, and Vishal and Manoj will, will show you how this particular stack really does provide, uh, a holistic solution for ai where other solutions out there may not. Um, and how all of those pieces move together.
More specifically, we have components like enterprise AI and the HCI components. That's not what we're gonna get into today. Those are foundations that are there, right?
And, and the strong Kubernetes platform that we've built allows us to run those applications and manage easily and deploy those cloud native applications. But what we really want to talk about is the data management foundation and the data platform itself. So we'll concentrate on Nutanix Unified Storage with Nutanix data lens.
And for those of you that that don't know, Nutanix does have an enterprise storage offering, which does file object and block, uh, within this offering of Nutanix Unified Storage. And then it also has cyber storage capabilities and data analytics and ransomware, uh, analytics for, uh, data lens as well. So one of the other things that I wanna set the table here and just let you know, is that there's been a lot going on even this week in terms of announcements coming out of the machine that is Nvidia, right?
So when we look at it, um, our solutions and everything that we'll talk about today have these underpinnings. We have a strong partnership with nvidia, um, and we will talk a lot more about GPU direct storage, um, our AI data platform for enterprise where our storage is NVIDIA enterprise certified. And then as well, we're also heavily involved in the, uh, NVIDIA enterprise AI factory, um, where you look at a full stack solution and we, we will come out with validated solutions there as well.
So, uh, just this past week actually in the keynote of GTC in Washington, DC Jensen mentioned, uh, a lot of the AI data platform announcements and where front and center in, in, along with a lot of other industry players in that space. Okay?
