What does it really take to power the AI supercycle – and who is building the foundation beneath it? In this episode of theCUBE + NYSE Wired: AI Factories – Data Centers of the Future, John Furrier sits down with Gary Niederpruem, chief executive officer of Forgent, just days after the company’s IPO and NYSE opening bell ceremony. Niederpruem reflects on the emotional milestone of going public and explains how Forgent is positioned at the crossroads of data centers, utilities and grid infrastructure. With nearly 80% of its business tied directly to powering AI factories, Forgent’s growth story offers a front-row view into how capital, energy and engineering are converging to fuel the next phase of digital transformation.
Niederpruem details Forgent’s engineer-to-order model, its role in designing end-to-end electrical distribution systems and its early engagement with customers months before construction begins. He connects surging CapEx to historical telecom build-outs, reframing today’s spending as infrastructure enablement rather than speculation. From transformers and switchgear to prefabricated power skids, the discussion also reveals how electrical architecture has become a strategic differentiator in AI-scale deployments. The interview also examines why energy now sits at the base of the AI “hierarchy of needs.” Anchored by a culture of customer focus, discipline and continuous improvement, Niederpruem outlines how Forgent aims not just to capitalize on today’s wave – but to build durable value for the AI era.
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Gary Niederpruem, Forgent
In this interview from theCUBE + NYSE Wired: AI Factories – Data Centers of the Future event, Glean co-founder and CEO Arvind Jain joins theCUBE’s John Furrier to unpack what’s really working in enterprise AI today and what comes next. Jain explains why knowledge access remains the first successful AI use case at scale and how Glean’s enterprise search brings AI into everyday work. He details the past year’s lessons with AI agents – from the need for guardrails, security, evaluation and monitoring to democratizing agent building so business owners (not just data scientists) can create production-grade agents.
The conversation dives into Glean’s vision of the enterprise brain powered by an enterprise graph, highlighting the importance of deep context, human workflows and behavior to reduce “noise” and drive outcomes. Jain outlines core building blocks – hundreds of enterprise integrations and a growing actions library – that let agents securely read company knowledge and take actions across systems (e.g., CRM updates, HR tasks, calendar checks). He discusses how organizations are standing up AI Centers of Excellence, prioritizing “top 10–20” agents across functions like engineering, support and sales, and why a horizontal AI data platform that unifies structured and unstructured data – accessed conversationally and stitched together via standards like MCP – sets the foundation for AI factory-scale operations. Looking ahead, Jain says Glean’s upgraded assistant is evolving from reactive tool to proactive companion that anticipates tasks and accelerates productivity.
play_circle_outlineCapEx Surge Fuels Global AI Data Center Build‑Out as $1B-Run‑Rate Firms Face Half‑to‑Gigawatt Power Needs
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play_circle_outlineForgent designs electrical distribution from substations into gray and white spaces
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play_circle_outline18-Month Early-Engagement High-Touch Power Solutions for Cloud, Colocation, EPCs: Transformers, Switchgear, Transfer Switches, E-Houses and Skids
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play_circle_outlineEnergy as foundational layer (AI Hierarchy of Needs); agnostic to power source
What does it really take to power the AI supercycle – and who is building the foundation beneath it? In this episode of theCUBE + NYSE Wired: AI Factories – Data Centers of the Future, John Furrier sits down with Gary Niederpruem, chief executive officer of Forgent, just days after the company’s IPO and NYSE opening bell ceremony. Niederpruem reflects on the emotional milestone of going public and explains how Forgent is positioned at the crossroads of data centers, utilities and grid infrastructure. With nearly 80% of its business tied directly to powering A...Read more
exploreKeep Exploring
How does the AI-driven CapEx build-out around data centers and the power grid relate to your company's growth and business strategy?add
What choices must customers make when selecting and designing a data center, and how does your company assist with the electrical distribution from the substation through the gray space to the white space?add
Who are your customers, and how does your company fit into the design and deployment of facilities like data centers (what products and services do you provide and at what stages are you typically engaged)?add
Where does your company sit in the energy-to-IT stack, and can your products adapt to different power sources and deployment models (e.g., utility/grid supply versus behind-the-meter generation for data centers)?add
>> Welcome back, everyone. I'm John Furrier, host of theCUBE, here at our NYSE studios. Of course, we have Palo Alto connecting Silicon Valley and Wall Street. It's our AI Factory series where AI leaders come in and share their vision for how the world of AI is being infused into all the applications in every single vertical, powered by the AI factories and the infrastructure build-out. Gary Niederpruem is here, chief executive officer for Forgent, just went public, rang the opening bell. Congratulations on your IPO, first of all. Big news there. It's a moment of consequence for the company. It's a milestone, a big one. Congratulations.
Gary Niederpruem
>> Yeah, I appreciate it, John. First trade was last Thursday, so that was a great day to be a part of. And then, to be back here today to ring the bell this morning was just a tremendous milestone event.
John Furrier
>> I really love when the IPOs go out and they celebrate with the bell ringing. Both balconies here at the NYSE were packed. People were going crazy. What was it like up there? As the chief of the company, seeing partners, friends, employees from the balcony, signing the book, doing all the ceremonial things, what was it like?
Gary Niederpruem
>> I got to tell you, it was almost a little bit emotional. So, we had the breakfast in the big boardroom earlier and we gave some remarks and that was a bit emotional. And then, standing up there and looking down and seeing family, friends, coworkers. We had 275 people representing Forgent. And so, we are a big values-based company, and so having as much family around us as we could was 100% the right thing to do. So, it was just a tremendous moment.
John Furrier
>> Great culture. I want to get into that a little bit later, but the real top story that you're hitting with your IPO and growth is the CapEx build-out that we're seeing in the industry around the growth of AI. Obviously, we're seeing kind of like second inning action. You got gen AI a couple years ago, three years ago, ChatGPT, but that got mainstream. But now, you're starting to see the real global applications. Society, work, the productivity numbers. Agents are super hot. NVIDIA's skyrocketed to be the number one supplier and stock, frankly, here. And the CapEx numbers are significant. People are scratching their heads, "What does all this mean?"
Clearly, it's the acceleration and the enablement of these AI factories, the data centers, which connects to the cloud. It's all growing. This is where you guys play. This is a major spot for you guys. Talk about where that fits into why you guys are growing.
Gary Niederpruem
>> Yeah. So, let me give you just 30 seconds of context. So, we're a little bit north of a billion dollar run rate business. About 50% of our business is in data centers, 30% is in grid and utility, the other 20% is industrial and other. So, the really nice interplay is we got 80% of our business that is tied to data center or the powering of the data center coming from the utilities and the grid. So, that is a tremendous backdrop for us, number one. And then, number two is I've been in the space for almost 30 years now, it's hard to believe. But I remember back in the day, we would talk about if it was a one megawatt data center, it was mind-blowing. And then, it migrated to 5 megawatt and then 10. And now, here we are all of a sudden, 30 years later talking about a half a gigawatt or a gigawatt facility that's going to be built. The scale, the speed, the complexity is like nothing I've ever seen. And to your point, the CapEx that is flowing in both to the data center side and the grid and utility side is right up our alley.
John Furrier
>> We were talking before we came on camera here around the CapEx, mind-blowing numbers. For insiders like us, we kind of go, "Okay, we can see the value that creation there," the enablement highly accelerates. It's not really disruptive, it's just enabling. It's accelerating more enablement. And we compared it to the telecom build-out. And every time someone asks me like, "John, is this out of control? Is this a bubble?" I go, "Bubble? I mean, look at the telecom build-out just on the CapEx." And they're like, "Well, I didn't really look at it that way." But if you think about the CapEx, what it will do... Okay, by the way, even for telecom too. So, you have the power, you have the connectivity, all these things at a flashpoint where AI supercomputing comes together, it's a perfect storm, and this is the dynamic. So, the CapEx is inline with the order of magnitude of the global scale of, say, telecom.
Gary Niederpruem
>> I totally agree with you. Not a lot of people draw that analogy or parallel, but I was in that telecom space for years as well. So, when you went from 2G to 3G, 3G to 4G, 4G to 5G, there was a huge wave of infrastructure that was always being built. And AT&T, Verizon, T-Mobile, they spend $50 to $100 billion a year collectively. So, to see people spending $100 billion now to build-out this next generation of infrastructure, to me is, yeah, it's a lot compared to what it used to be. But when you look at it, what it's going to do and how it's compared to some of that telecom build-out, I don't think it's that out of skew.
John Furrier
>> Yeah, and I liked your strategy with the power and the energy piece, because if you look at that compressed nature of the speed to build-out, the rush. The demand is there, so that kind of takes the bubble conversation off the table because there's clearly demand, but it's not easy. So, you go back in the data center days, think internet, "Oh, yeah. Here's a facility. Get some real estate deal. I got power, a megawatt. Okay, that's huge or maybe less. Throw a couple bunch of racks in there."
Even Amazon Web Services early days was a bunch of servers and a data center, it wasn't really complicated, but then they engineered it. So, we're in this engineering cycle, not just get the space, turn the lights on, plug it in and go. It's a little bit different. Can you explain the nuances now around the complexity and the importance of why data centers are being built in a different way?
Gary Niederpruem
>> Yeah, I think you have to do it in a different way is number one. Number two is it is highly bespoke for what we see. So, from our business specifically, we are an engineer-to-order type of company. So, we build custom and design, custom products. 90% of our portfolio is in that custom-to-build scale. And the reason that is there is always something changes. I call a data center, either a snowflake or a very heterogeneous environment. If it was a homogeneous environment where you had one application and one server for that application, you could do things in a standardized way, but you have different power inputs, you have different servers, you have different applications. There's things that are always changing and dynamic, that heterogeneity is what really drives our customer base to say, "Almost everything needs to be custom." And so, it doesn't have to be a totally different custom setup, but I want to design something, I want to replicate it a few times, then I got to go back to beginning to design again because there is always something changing on the input or the output.
John Furrier
>> I was talking with Prasad who manages all Amazon's deployments in the regions, North Carolina, all the big deals. And he said, "John, the thing that's different," I'd love to get your reaction, he goes, "Every environment has a different power envelope and uniqueness to it." I go, "What do you mean?" Then he explained like, "I can get power, but I also need diversity of power sources. It's not just electricity, there's other stuff." And then, they also have the sustainability objective. So, the power is complicated. Explain how you guys make that work because it's not like rolling into town and saying, "Hey, you got some data center space here, can I just buy it or use it?" You got to really think through what the geography is looking like, the town or cities, the regions. Talk about that nuance.
Gary Niederpruem
>> There are. So, we did some high-level math and said, "From the time that a customer picks the application, what other choices do they need to make just on the data center piece?" And it's geography, it's redundancy, how many number of racks do you want in there? Where is it located? What's the heat load? So, there are 4,000, 5,000, 6,000 choices that a data center company has to make, that's a lot of permutations and combinations to get there. So, what we do is we can start, because we have a grid in that utility business, we start with our customers right near their substation. And so, from that substation all the way into the gray space, all the way into the white space, we can help them design that electrical distribution system, which is so critical. You can't move power from point A to point B without electrical distribution here. So, we are an old-fashioned industrial company, but wired to this technology sector, which is the great intersection for us.
John Furrier
>> It's a great intersect. Explain for the folks who are trying to unpack and I guess demystify the fog of how complex it is, what is your customer base and your growth strategy? How do you do business? Take us through some of the mechanics and key metrics that you guys do in your business.
Gary Niederpruem
>> Yeah, because we are a very engineer-to-order company, it's a very high-touch model, so we're very direct with our customers. That is where it starts. Very direct, very engineering, very technically-oriented. So, we will help our customers design that one-line diagram, which is that entire power flow from point A to point B, not many people in the space do that. So, we provide very, very deep engineering skills. Then, we will ultimately provide them a solution. Then, we will back into our products that we think fit for that solution for that design that we design.
John Furrier
>> And those are data centers? Are they clouds? I mean, who are the customers?
Gary Niederpruem
>> So, we have cloud customers, we have neocloud customers, we have co-location customers, and then we also work very closely with the EPCs and the general contractors that are building those facilities for those other end users. So, it's a very complicated, actually, go-to-market, because you have end users, you have the design contractors, general contractors, engineers of record. You have to influence them all to get them to the right spot.
John Furrier
>> That's awesome. And this is where the demand is. Take us through a deployment. Where do you guys fit into the build-out? What are some of the things that's unique to you guys that make it all work?
Gary Niederpruem
>> Yeah. So, when we're doing our job right and engaged early with our customers, we're probably 18 months ahead of when they actually need our product. So, sometimes they haven't even bought the land. Sometimes they're just clearing the land. We want to be as early and often as in that engagement. From there, we will help them design that electrical diagram, that's maybe nine months. From that point in time then, they will probably cut us a purchase order for our products. So, what we do is anytime you're going to step voltage up or step voltage down, you need transformers to do that.
And so, we have a big transformer business. As you get closer to the actual facility, you have to control that power, that's what our switchgear does. If you have a generator on site and you lose utility power, the generator kicks on, we have transfer switches. And then, ideally you want to take as much of that and put them in e-houses or skids to prefabricate, take labor out of the field and put it into our factory. So, those are the four big things we do, but it is all about that electrical distribution change.
John Furrier
>> You're like an inside the AI factory.
Gary Niederpruem
>> Oh, that's 100% what we are.
John Furrier
>> So, a lot of front-end professional services on the engagement, on the design side, engineering. And then, they go with construction, deployment and it's up and running?
Gary Niederpruem
>> That's exactly right. That's exactly right.
John Furrier
>> Talk about the demand. I mean, we've been covering Coreweave, Nebius, Lambda. They're all doing great. Amazon, Google, Oracle, Microsoft. The demand is off the charts. You're starting to see segmentation where the notion of cloud, or whatever, maybe legacy cloud, if that's a word, where the workload demand is so high for AI, you're starting to see some segmentation, almost policy around workloads. And I think a lot of people don't know this, but this is driving a lot of the demand for the neoclouds or data center market that was either being bought completely by the clouds, but now renting or buying GPUs because the supply from say NVIDIA might be down. So, they're starting to think about, okay, I can run tier-two workloads through an abstraction, and so that's going to fuel the data center market. That's my thesis. Do you agree with that? I mean, do you see that same pattern around the growth is going to spill into a distributed computing cloud-like environment? So, I mean, I'm on Amazon or Google, it looks the same to me. I'm getting GPUs, my apps work, maybe it's not the one second latency or nanosecond. Maybe the big stuff stays on the super expensive gear. Still needs power.
Gary Niederpruem
>> I'm 100% in that same camp. So, I think there's two points. One is what people also don't realize is just the cloud growth itself is what's fueling a lot of the spend going on. The AI piece is like a cherry on the top. So, from our business specifically, most of what we're shipping today is just still for cloud demand. The AI piece just started to come in the backlog in the last quarter or two. So, one is people need to understand the cloud base in and of itself is a really healthy growth profile. The AI piece is just the cherry on the top, that's number one. Number two, to your latter point, to me, it all starts with the applications. So, I remember the first time we started working with cloud folks probably 15 years ago. And the best example was look, if you search on Google, you're going to be in one data center. That's probably not as redundant. Then, you're going to go to checkout and buy something in that you're going to move to a different data center that has more redundancy. Then, when you actually go to transact financially, you are probably in a third data center that has better security, that has higher level of redundancy. So, to me, it all starts with the application and AI is the exact same way for me.
John Furrier
>> I love that because that speaks to the topic of... At the end of the day, we're talking about distributed computing operating system theory. Who cares where it is as long as it does its job and you go to the resource of interest and you scope the workload policy, critical nature of it? If it's a high-yield transaction, it gets tier-one resource. I mean, it's like just deciding where to go.
Gary Niederpruem
>> I mean, not all applications are created equal. And so, therefore, not all data centers are created equal, therefore, not all electrical engineering systems are created equal. That customization rings through at every layer.
John Furrier
>> Gary, talk about the growth strategy, because you're going to knock down the wave we're in now, which is a great demand curve. So, congratulations. We are starting to lay down some content around what we see as the next big thing, which is the edge. AI factories are the big honking data centers, data centers going to get built out, more resource nodes on the network. I think you start to see little action at the edge, smaller boxes, but bigger edge, maybe a metro factory. New York City could have its own little system, could have its own cloud. A lot of power in Manhattan. So, have you thought about like beyond the data center, what's your vision for growth?
Gary Niederpruem
>> I think the exact same evolution will happen as did telecom, as did cloud, which is you started in telecom with central offices and then you went to smaller nodes. I think when you started with cloud, you started with the big cloud facilities, then you went to a distributed architecture called edge. I think that AI is in the same thing. We have these massive AI factories that are being built now, which are centralized. And as time and maturity happens, more and more things will get pushed closer to the consumer for latency, for speed, for a variety of reasons. And I think that distribution is going to happen in AI. I think we're still focused on the centralization. So, I think we got a couple years before we get to the decentralized piece. I have no doubt to think that those other parallels won't repeat itself in edge.
John Furrier
>> And they'll work in tandem.
Gary Niederpruem
>> 100%.
John Furrier
>> They're new.
Gary Niederpruem
>> You need both. You need both.
John Furrier
>> So last year... Or this year I should say. It was actually last year, but a couple months ago. Within the year, Jensen Huang put up on stage at the GTC event in DC, a political spot event he had, because there's a lot of politics involved. He put up a slide and he called it the AI Hierarchy of Needs, kind of a playoff Maslow's Hierarchy of Needs. At the bottom was energy.
Gary Niederpruem
>> Yes. Yes.
John Furrier
>> Food and shelter for us humans.
Gary Niederpruem
>> That's right.
John Furrier
>> And so, energy is now bounding all value. This is where you play. And above that, everything builds on the stack on top. What's your thoughts on that and how does that evolve over time? Given your current business you're in now, do you have to think differently about energy and power as you move down the evolution?
Gary Niederpruem
>> Yeah. So, it's so funny you mentioned that. I have a screenshot of that exact diagram in my phone right now, and I do. I think it's one of the most accurate things ever because it does. It starts with energy and infrastructure. Then, you can go to the IT layer, then you can go to the servers, then you go to the application layer. I think that's exactly right. We are the foundation of all of that. And because of that, we get involved with the utilities and the grid folks that are providing the power. The other thing that we're seeing quite a bit is if a customer can't wait for the utility to deliver that power, they're taking matters into their own hands by building behind-the-meter natural gas turbine plants or something like that. That is a great use case for our products as well. So whether it's coming from utility and grid, which is the supply, or if it's coming from the demand, which is the data center, we are at the epicenter of both of those.
John Furrier
>> So, you're saying you can flex with whatever power evolution comes to the table?
Gary Niederpruem
>> Our product set and our manufacturing facilities are 100% fungible. So, whether or not we need to vector more towards grid or utility or data center, we can do that. The other thing is that we are also agnostic to the utility company, whether it's coal fire, whether it's natural gas, whether it's solar, whether it's wind, whether it's nuclear, we're agnostic to the power source. The fundamental pieces are you have to move power from one point to the other and you can't do that without our gear.
John Furrier
>> All right. Talk about the secret sauce and the culture. I mean, every company has one. Intel's was Moore's Law, NVIDIA's software CUDA, co-design, and there are a lot of first principles. What is your secret sauce for the company and what's the culture like?
Gary Niederpruem
>> Yeah, I thought a lot about this. I think my job is not that difficult. I have three things I have to do. One is I have to enforce the culture. So, we want to hire good people. We hire for EQ as much as we do IQ, that is a really big deal. You need to know how to communicate, treat people fairly. That is a big deal inside of our company.
John Furrier
>> And you got the professional service, you're a white glove service. You need to have that-
Gary Niederpruem
>> They're out in front of customers all day long. That's exactly right. So, my number one job is to make sure we continue to evolve the culture. Number two is we need to make sure we take care of our customers. And so, we're hugely customer focused, hugely customer-centric. And then, number three is once we get the culture nailed down, once we get the customers nailed down, we can't become complacent. Nick Saban won a couple years ago.
John Furrier
>> I love that.
Gary Niederpruem
>> They won the national championship. He called his staff in the next day at 7:30 AM to watch film. I don't want to be maybe quite that maniacal, but that's a great example of not becoming complacent. So, culture, customers and complacency are the three keys.
John Furrier
>> And he also quotes from good to great. He wants to manage people on the bus or off the bus, which I love that line too.
Gary Niederpruem
>> 100%.
John Furrier
>> He loves culture and he's got the winning culture.
Gary Niederpruem
>> 100%.
John Furrier
>> All right. Final question. I know you're super busy. Thanks for spending the time. I love unpacking the data centers. Not often we get experts in the factory build-out phase, so thanks for sharing. What's next? It's a moment of consequence going public. You're here celebrating with your team and family and friends. It is a moment. What's next? You're going to celebrate? Take a little break? What's the next milestone for you? What are you focused on?
Gary Niederpruem
>> Yeah, I think two things. So, one is we had a breakfast and I addressed the employees this morning and I said, "Look, our goal was not to get here. Our goal is to stay here and thrive here. So, it's a great moment, soak it up, and I want you to celebrate for 48 hours. And then, we're going to come in on Monday and we're going to start taking care of our customers better, designing better, manufacturing better."
So, that is what we're going to do. We're going to celebrate for 48 hours, come Monday morning, the goal is not just to be here, the goal is to stay here and thrive here.
John Furrier
>> Well, congratulations and thanks for coming on theCUBE. Appreciate you.
Gary Niederpruem
>> Appreciate it, John.
John Furrier
>> Culture, winning, but also, having the kind of EQ in a data center build-out, it's not for the faint of heart, but it's going to accelerate the enablement of AI, which is going to be a major value to people, business and society. Again, more tokens come out of these factories, the more intelligence is built. You got to have that foundation here. Forgent's doing it, bringing the power to the table. This is theCUBE. Thanks for watching.
John Furrier