Name: Dan Wright, Armada
Uploaded: 2025-09-26T17:00:00.000Z
Duration: 12 min

More from theCUBE + NYSE Wired: AI Factories - Data Centers of the Future

Gemma Allen

Host, theCUBE + NYSE Wired

theCUBE

Dan Wright

Co-Founder & CEO

Armada

Info

Dan Wright, Armada

Gemma Allen

Host, theCUBE + NYSE Wired theCUBE

HOST

Dan Wright

Co-Founder & CEO Armada

Dan Wright

>> Palo Alto Studio connecting Silicon Valley and Wall Street. I'm John Furrier, co-host of theCUBE here with Dave Vellante, my co-host.

Gemma Allen

>> Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen, co-host of NYSE Wired. It's AI Factories. And today we are going to talk about AI factory in a box on the edge. Joining me now to unpack exactly what that means is Dan Wright, co-founder and CEO of Armada. Welcome, Dan. Hey, thank you. Great to be here. So it's not your first rodeo at NYSE Wired. I know you've been on the show before.

Dan Wright

>> Yes.

Gemma Allen

>> But when we catch up with folks these days, it feels like a century has gone by in just a couple of months.

Dan Wright

>> It's amazing.

Gemma Allen

>> Things are moving so quick, right? Talk to me a little bit about what's happening at Armada, Dan. What has been going on since you were last on the show?

Dan Wright

>> Well, it's crazy. When we started Armada, it was about 3 and a half years ago. There was no Anthropic, there was no xAI, there was none of these other labs out there. But we knew that there would be a lot more of them and that companies would want to use those models. And the biggest constraint was going to be infrastructure and energy. And so what Armada does is we bring these AI data centers, AI factories in a box to the energy wherever it is, and enable sovereign AI all over the world. And we're scaling extremely fast. We actually just today announced our 10-megawatt Galleon. We call our modular data centers Galleons, like ships. And it's called Orion.

Dan Wright

>> Okay.

Dan Wright

>> And that's been getting a ton of interest, inundating my team with new leads wanting that product. And we're deploying these all over the world. And then the other thing, obviously, we're here at NYSE. We're announcing with NativX COIL, the free open exchange where you can invest in compute the same way that you can invest in other commodities like electricity.

Gemma Allen

>> And it's all down to Megawatts, right? We had those guys on the show earlier.

Dan Wright

>> Yes.

Gemma Allen

>> Cole and Pawel, they're going to commodify exactly what that means.

Dan Wright

>> But that's right.

Gemma Allen

>> Let's talk a little about what's happening on the edge. We talk to a lot of companies in this space. I feel like it has grown a lot even since just this time last year. Yeah, there's a lot. It was a space that was relatively unknown, somewhat sketchy. Yeah, sketchy terrain too.

Dan Wright

>> Yes.

Gemma Allen

>> But now it seems like it's a very competitive space. There's a lot happening. Yeah, I think a lot of folks are starting to realize, okay, we're moving from, needing inference in data centers and, in these kind of mass outlets to actually also needing that same level of deterministic to probabilistic on the edge, right?

Dan Wright

>> Yeah.

Gemma Allen

>> Talk me through some of your customer cases. Give me some examples of customers that you maybe weren't even working with a year ago.

Dan Wright

>> Yeah. So we call Armada the hyperscaler for the edge. And what we've done is we've continuously redefined the edge. When we started the company, when people talked about the edge, they meant the edge of the cloud providers' networks.

Dan Wright

>> Mm-hmm.

Dan Wright

>> But that only covers about 30% of the world. There's 70% of the world where there's oil rigs, there's mines, there's battlefields, there's natural disasters where first responders need to use data from drones in real time to save lives. And that's our focus as a hyperscaler for the edge, is bringing it where others won't and filling all the gaps in infrastructure. And just to give you a few examples, we work with, for example, the first responders in Alaska, helping them process data from drones in real time. They used to have 28 hours of latency because there were no data centers in Alaska.

Gemma Allen

>> Wow.

Dan Wright

>> And that's to respond to avalanches and floods. Avalanches and floods don't wait 28 minutes, let alone 28 hours. So you have to be able to respond in the instant. We work with the US Navy. We deployed last year offshore, running completely on ship's power, air-gapped at the edge. We are now deploying with allies. We were public about some work we did in the Middle East when the AWS data center got hit. We were deploying these to enable resilient distributed compute. And then energy, for example, we work with Aker BP in the Nordics and Aramco. And then with our larger form factors like the Leviathans, which are 2 megawatts a unit, and the Orions, which are 10 megawatts a unit, a couple of real-time examples. We're actually here today with Fossefall, which is a big company coming out of Norway that wants to do a gigawatt of capacity using mainly hydroelectricity, almost all hydroelectricity by 2030. And so they're deploying our Leviathans in order to scale up quickly because we can deploy in months versus years with traditional data centers. And then, on the other side in Australia, we're deploying with WinDC. Last year they had 7.2 terawatt hours of curtailed energy. They've got tons of wind and solar energy.

Gemma Allen

>> Wow.

Dan Wright

>> And so what we did is we just bypassed the grid, which is the bottleneck. We took the compute capacity to the energy where it lives to enable AI factories there in the outback.

Gemma Allen

>> Wow. Let's talk about the tech and what's unique on the real edge, right? The true edge, like these very remote areas. I actually met BG last night at an event. Yeah. Funny guy, right?

Dan Wright

>> Yes, very funny.

Gemma Allen

>> Marek, our Norwegian friend. But we know that the edge has its own constraints and its own, I guess, also opportunities from the perspective of lower power, lower compute, right? You don't necessarily need, the same brand of H100 that you need in other places. That's right. You don't need a Toyota to, you know, drive on a racetrack,

Dan Wright

>> whatever.That's

Gemma Allen

>> right. Whatever analogy has been given. Talk me through kind of what you're seeing from the perspective of what that means for diversification of, you know, the tech stack.

Dan Wright

>> Yeah.

Gemma Allen

>> What are you seeing? You obviously work with NVIDIA. You work with a lot of those, I'm sure, large chip players. Break it down though. explain to me, what— how are things trending there? And then I want to get into tokenomics and obviously NativX. But first of all, yeah, what are you selling.

Dan Wright

>> Yeah. So first of all, what we sell is AI in a box, right? So we do the full stack, we do the hardware, we do the software, we do GPU orchestration. We have a marketplace of all the latest models. We run those air-gapped at the edge. If you've got your NVIDIA chips already or your Dell servers, we do kind of all of the integration, deliver it as a turnkey solution, and then we do all the critical infrastructure monitoring and management. So it's as easy as the cloud, but at the edge, or what we call the new edge, that 70% of the world that doesn't have the big hyperscale data centers. And, it's actually really good timing because the chips, every generation, they're getting more compact. They're getting more powerful. And so in a given box, you can just do a lot more. And companies want to do a lot more. A lot of them, like, let's take, Aker BP, kind of cutting-edge energy company in the Nordics. They want to do fully autonomous rigs over the next few years. You're going to need a lot of AI. You're going to need a lot of robotics. They have tons of data on those rigs, but you have to be able to deploy the capacity there locally behind their firewall because they also are very sensitive to IT cyberattacks. They have a hard segregation between IT and OT. And so we're a really good fit there. But the Galleon family is perfect because we say, okay, well, what workloads do you want to run? And then we have a form factor for whatever you want to do. If you want to do something at massive scale with Orion now you can scale into the hundreds of megawatts. And if it's more of a, hey, I need maybe a distributed compute kind of hub and spoke solution where I've got some large nodes and some very small nodes just for inference, we can do that too.

Gemma Allen

>> We've been talking a lot about how you measure performance, how you measure output, right? NVIDIA's.

Dan Wright

>> Yeah.

Gemma Allen

>> Perfect conversation around that because those guys are essentially saying it's not GPU per hour, it's like megawatt per unit. It's how much AI am I getting for my GPU, right?

Dan Wright

>> That's right.

Gemma Allen

>> As opposed to, which is, again, I think the industry is kind of catching up to that.

Dan Wright

>> That's right.

Gemma Allen

>> But when we think about the world of the edge, it's actually quite unique because again, you talk about various form factors there. You're in very difficult terrain though. You probably have challenges with latency and resilience and performance that are very unique to the environment and location you're in, right? So creating that opportunity to connect. But again, when the market has been selling everything in kind of a ubiquitous way, it does kind of create somewhat of a challenge. This opportunity with NVIDIA AI Grid, how do you unpack that? You know, we talked to the guys, does Jensen want this?

Dan Wright

>> Yeah.

Gemma Allen

>> Made an interesting—

Dan Wright

>> Absolutely.

Gemma Allen

>> What do you think?

Dan Wright

>> I think when you look at it, some of the gigawatt-scale projects are coming up against some headwinds, right? There's a lot of pushback against those. But we look at it and say, and we actually did a white paper on this last year before a lot of that was happening, there's 6 gigawatts plus of stranded energy just in the US alone.

Gemma Allen

>> Wow.

Dan Wright

>> And then, we talked about 7.2 terawatt hours of curtailed energy in Australia and lots of parts of Europe. It's the same thing. So there is a lot of power available, but it's about co-locating the compute with the power. And then with NVIDIA AI Grid, what we're doing is we're actually creating a market that makes these projects easier to monetize, right? Which ultimately unlocks project financing, which allows them to move faster, which is very, very important because the US also needs to think about it from a national perspective. We gotta win this AI race. It's the one race that you can't lose. And so I think using our capital markets and then what Armada is doing is finding that energy wherever it lives and sort of being the infrastructure layer in between them. Jensen's excited about it, but we're excited about it 'cause ultimately I think this is a way that we can win. And it's like all of the benefits of AI data centers with none of the drawbacks. We use behind-the-meter power so it doesn't impact ratepayer electricity bills. It's a closed cooling system, so you're not impacting cooling. But what you are doing is you're creating a lot of new jobs and you're also creating a lot of economic growth for these states and for the country.

Gemma Allen

>> And when you think about this future world, we have GPU as a commodity. We have a benchmark that we're measuring against from the perspective of how that impacts your customers, your clients. It also gives them a level of predictability and expectation, right, in what's called like good put. But it also gives them like a financial predictability. Yeah. How and what are you kind of hearing? Because we hear a lot about tokenomics, the stresses, the fact that it's somewhat of a wild west. Perhaps people are getting like misaligned product sales, right? in terms of what they need versus what they're buying.

Dan Wright

>> Yeah.

Gemma Allen

>> Well your industry is obviously very niche. I'm sure those relationships are extremely tight.

Dan Wright

>> Yeah.

Gemma Allen

>> What are you seeing and kind of feeling in the market?

Dan Wright

>> Yeah, what we're seeing is like a lot of companies are interested in using some of the capacity for their own internal use cases. All of them are trying to do more with AI. They're trying to do more with automation. But then if you can say on top of that, if there's capacity that you're not using, you can immediately monetize it and create new revenue streams. That's very compelling, right? You think about a lot of energy companies. We work with a lot of energy companies. A lot of them were dipping their toe in the water when it came to Bitcoin. But then obviously there's a lot of volatility that can come with that. The beautiful thing with AI is it's higher margins and the curve is going up and I don't see any end in sight because all of these AI labs and these latest models, they're just hungry for the compute. And so if you can just make that available and also unleash the public markets, there's almost endless demand.

Gemma Allen

>> Okay, so last question to you, the road ahead. So you mentioned you came this close to ringing the bell at some point before Cisco swept in with AppDynamics.

Dan Wright

>> Yes.

Gemma Allen

>> And I'm sure it was a very lucrative opportunity too. What is the plan here for Armada? you mentioned you seem to have a huge TAM, some big brands you're already in partnership with. Are we going to see you ring the bell at the NYSE

Dan Wright

>> then?I mentioned our mission is to bridge the digital divide and be that hyperscaler for the edge that is the hyperscaler for the 70% of the world that doesn't have these data centers today. That's a huge vision. And if we fulfill that vision and that mission, I think we're going to end up here at some point. So we're looking forward to that.

Gemma Allen

>> Well, please invite us to the party.

Dan Wright

>> Yeah, absolutely.

Gemma Allen

>> Dan Wright, thank you so much for joining us on NYSE Wired.

Dan Wright

>> Thank you very much for having me.

Gemma Allen

>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is NYSE Wired's AI Factories. Thanks for watching.

Dan Wright, Armada

Dan Wright

>> Palo Alto Studio connecting Silicon Valley and Wall Street. I'm John Furrier, co-host of theCUBE here with Dave Vellante, my co-host.

Gemma Allen

Dan Wright

>> Yes.

Gemma Allen

>> But when we catch up with folks these days, it feels like a century has gone by in just a couple of months.

Dan Wright

>> It's amazing.

Gemma Allen

>> Things are moving so quick, right? Talk to me a little bit about what's happening at Armada, Dan. What has been going on since you were last on the show?

Dan Wright

>> Okay.

Dan Wright

Gemma Allen

>> And it's all down to Megawatts, right? We had those guys on the show earlier.

Dan Wright

>> Yes.

Gemma Allen

>> Cole and Pawel, they're going to commodify exactly what that means.

Dan Wright

>> But that's right.

Gemma Allen

Dan Wright

>> Yes.

Gemma Allen

Dan Wright

>> Yeah.

Gemma Allen

>> Talk me through some of your customer cases. Give me some examples of customers that you maybe weren't even working with a year ago.

Dan Wright

>> Mm-hmm.

Dan Wright

Gemma Allen

>> Wow.

Dan Wright

Gemma Allen

>> Wow.

Dan Wright

>> And so what we did is we just bypassed the grid, which is the bottleneck. We took the compute capacity to the energy where it lives to enable AI factories there in the outback.

Gemma Allen

>> Wow. Let's talk about the tech and what's unique on the real edge, right? The true edge, like these very remote areas. I actually met BG last night at an event. Yeah. Funny guy, right?

Dan Wright

>> Yes, very funny.

Gemma Allen

Dan Wright

>> whatever.That's

Gemma Allen

>> right. Whatever analogy has been given. Talk me through kind of what you're seeing from the perspective of what that means for diversification of, you know, the tech stack.

Dan Wright

>> Yeah.

Gemma Allen

Dan Wright

Gemma Allen

>> We've been talking a lot about how you measure performance, how you measure output, right? NVIDIA's.

Dan Wright

>> Yeah.

Gemma Allen

>> Perfect conversation around that because those guys are essentially saying it's not GPU per hour, it's like megawatt per unit. It's how much AI am I getting for my GPU, right?

Dan Wright

>> That's right.

Gemma Allen

>> As opposed to, which is, again, I think the industry is kind of catching up to that.

Dan Wright

>> That's right.

Gemma Allen

Dan Wright

>> Yeah.

Gemma Allen

>> Made an interesting—

Dan Wright

>> Absolutely.

Gemma Allen

>> What do you think?

Dan Wright

Gemma Allen

>> Wow.

Dan Wright

Gemma Allen

Dan Wright

>> Yeah.

Gemma Allen

>> Well your industry is obviously very niche. I'm sure those relationships are extremely tight.

Dan Wright

>> Yeah.

Gemma Allen

>> What are you seeing and kind of feeling in the market?

Dan Wright

Gemma Allen

>> Okay, so last question to you, the road ahead. So you mentioned you came this close to ringing the bell at some point before Cisco swept in with AppDynamics.

Dan Wright

>> Yes.

Gemma Allen

Dan Wright

Gemma Allen

>> Well, please invite us to the party.

Dan Wright

>> Yeah, absolutely.

Gemma Allen

>> Dan Wright, thank you so much for joining us on NYSE Wired.

Dan Wright

>> Thank you very much for having me.

Gemma Allen

>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is NYSE Wired's AI Factories. Thanks for watching.