DigitalOcean Holdings, Inc. ($DOCN)

Welcome to BofA's Global Tech Conference Day 2. I know it's a session after lunch, but that's why we got Matt over here to keep you all on your toes and stay awake. Welcome to DigitalOcean. We have the CFO, Matt Steinfort. Matt, Thank you for joining us. You guys have done an incredible job here over the past few years in changing the entire sort of model of the company going from a developer cloud to what you are today. So do you want to take a minute to maybe talk about what has changed over the last couple of years, and we'll get into Q&A.

Yes. Thanks, Wamsi, and thanks for having me, and thanks for the nice walk-up music with a little Colorado theme, I appreciate that. You and I were talking about before the session, how much the company has changed in the last couple of years and how the narrative has changed in terms of the questions that we get. A couple of years ago, we were still the third largest cloud by customer count, but we view it as kind of the smaller kind of toy cloud that was largely targeting developers and small kind of businesses. And I think that narrative there was, okay, don't your biggest customers tend to just go away from you because they get -- they outgrow you and they graduate. And we spent a lot of time. Literally, the #1 question, like the hard question when we would prepare for these sessions was -- the number 1 question was, why do you guys exist? Why can't the hyperscalers do what you guys do, and we had to spend a lot of time explaining that we have carved out a niche, and we serve an underserved portion of the market in the core cloud by those customers who aren't well served by the hyperscalers because they need more attention, they're digital native and they need more care and feeding, they need simpler, they need less requirements for long-term contracts and those kind of things. And -- but we couldn't explain away the fact that, yes, we did have a challenge, a leaky bucket in our top customers. And so you roll that forward to today, and not only have we fixed that particular issue in the core cloud, we're now our $1 million-plus customers are growing. I think it's like 180%, and we hadn't had any churn in the last 4 quarters in that bucket. So we've fixed that challenge. But we've also launched and taken the same kind of fundamental value proposition into the world of AI. And we've developed a very compelling full-stack AI native cloud that is resonating incredibly well with our AI customers and the AI customer revenues growing 220%. And we built a very strong business there with a number of marquee inference oriented customers. So very, very different kind of business in just 18 to 24 months and required a lot of development, required retooling the leadership team at all levels of the company and kind of rediscovering our roots around focusing on the technology customers and the end experience but not on the individual single developer, but more on the larger digital and AI native companies. So it has been a dramatic shift.

Yes. No, sure has. Maybe it's getting reflected in the guidance that you provided, which you have opt a few times now. And I guess as you look over the last, call it, I don't know, 6 months or 90 days, like what has really changed in what you're seeing in discussions with customers that's giving you the confidence to keep adding this power and expansion plan that you'll have that you have communicated to investors and also taking the guidance up now to like 4% to 50% for next year?

Yes. It's the traction that we're getting with the customers, this is kind of -- it's a virtuous cycle, right? So when we won character a while back, that was the first kind of marquee recognizable name that we had won. And we had a lot of smaller customers who are interesting. But winning character gave us credibility in the market to be able to secure the cursors of the world and start to win some of their business, like hippocratic and idiogram and others. And the more we learn from them the more we can develop our software in a differentiated way and build on the platform advantage. And the more we do that, we're getting more attractive customers are coming on. So it's just -- it's snowballing. And so that gives us the ability and the confidence to take down incremental capacity. And as we're getting more experience deploying that capacity, we're having more confidence in our ability to execute on the time lines and turn up some of the new technology like liquid cooling is very new for the industry. And the first ones that we turned up are -- in fact, the first of the data centers we turned out this year was air cooled. So it was like that. We're just now getting into the liquid cooled, but we're delivering even our second data center that came on in April, which was fully liquid cooled, came on ahead of schedule. So we're just getting more confidence in our ability to execute. So that's kind of 1 part of the guide. But the other part is just the customer traction that we're getting and the reaction we're getting and the demand signals that we're getting from those customers and the customers in the pipeline is very compelling and enabling us to really lean in.

Yes, you've gone from like 40-plus megawatts and added like another 30-plus now, like 60-plus more. How should we think about this incremental 60, when does that come online?

Yes, it comes online over the course of '27. So it's not entirely at the beginning, and it's not back-end loaded. So think about it, it's going to come on. It's 4 different data centers. So there's diversity there of providers and locations. So we feel good about our ability to manage those, and they'll come on over the course of the year. We'll provide more clarity when we get to the '27, the kind of more formal guide. We feel really good about the providers and the partners that we have. They're all very experienced data center operators. These are generally existing facilities where they're building out a data hall for us. Where there's existing campus, where there's a building that's like a shell that's ready to go and they just need to kit out for us. We feel good about the operational execution risk associated with that.

Yes. It's not like you're targeting a gig of capacity. These are much more measured sort of incrementals. But even despite that, it looks as though the market is relatively tight in terms of being able to procure whether it's servers, whether it's everything in our power, it's getting like all the liquid cooling in place. So are there any particular constraints that you see or what are maybe the tightest constraints that are going to determine how that 60 megawatts gets rolled out?

Yes. And I mean it's -- what is it, it's June now, which is crazy, but it's June, and we just announced 60 megawatts will come online in '27. So we're 12 to 18 months in front of that. So there's clearly -- the data center providers need to deliver on schedule. Like I said, this is not data center capacity being built from dirt, right? This is existing facilities. Power is already there. So there's not as much risk there, but they still need to kit it out. The equipment side is less a scarcity thing than it is a timing and cost, meaning you can get the capacity [ pick that are quantum ]. So like you want the amount of GPUs that we're buying, you can find them. Multiple OEMs have them like we work with Dell and Super Micro and HP and Lenovo. We work with a lot of them. The question is, can I get it to you when you want it. And can they give you some kind of certainty on the price, because the cost -- the component costs clearly are going up. And so that's something that we have to deal with. But it's less of can you get it than it is can you get it when you want. And we've been pretty good about our relationships -- working our relationships with the OEMs and the evidence of that is we turned on the 6 megawatts of the 31 we're deploying this year. We said second quarter, when we provided guidance, we delivered in March. The second of the 3 is a 10 megawatts, we said second half, and we delivered it in April. So -- and when we say we delivered it, when we deliver it, it comes with the GPUs are right behind and the CPUs are right behind it.

Yes. Okay. That's helpful. How much visibility do you need to sort of go ahead and put this incremental capacity and sign these data center leases, like what sort of visibility do you have from your customers, both in terms of duration and as well as sort of magnitude?

Yes. Well, we've been, I think, very clear multiple times certainly, the demand that we have right now from our existing customers and could fill up the capacity that we have. And that we've got 3 to 4x the capacity or the demand and the capacity that we're bringing online. And that's what gives us the confidence and the signals that we're getting from our customers, the feedback that they're giving us on, the impact we're having on their total cost of ownership and some of the new capabilities that we've announced that are very compelling to our customers, many of them developed jointly with our customers, like the infras router capability. All of that gives us the confidence. Plus, the market opportunity is just -- I mean you're seeing -- you had a number of other companies here at your conference that are doing very well, very good companies that are also seeing similar demand. Like the demand in the market is, I won't say limitless, but it's -- there's certainly not enough capacity to meet the demand that's out there right now. And I think we're benefiting in that customers are beginning to understand the difference between coming to someone who can provide them a full set of inference capabilities with a full cloud stack next to it versus someone who can provide them with access to bare metal, which is valuable, but requires you to do a lot more and invest a lot more in. Our customers tend to not want to spend their effort and their resources worrying about like the infrastructure level and they want to focus on building their own software.

Yes. That makes a lot of sense. Matt, so you just said demand is like 3 to 4x. I mean literally where -- what you're able to potentially scale to. Why not -- why is 60 megawatts the right number in terms of getting when demand is like so strong?

Yes, I think that's probably the single question that everybody in the audience has got on their mind as well. 60 is what we had signed as of the last earnings. So that -- there was no magic number there. It was the number that happened to be signed at the time that we did earnings. And what we had said is we're continuing to actively evaluate incremental capacity for '27. We're looking at '28 capacity already. Clearly, we're looking at how do we grow even faster. So part of the executive team and the Board, 1 of our primary focuses is exactly that, like how fast can we go and that has -- there are a lot of dimensions to that. Like how fast can you go without being too highly levered. Like, okay, well, there's a throttle we have to have. And fortunately, we've demonstrated the ability to tap into the equity markets and do things to give ourselves an incredibly strong and flexible balance sheet. It has implications on, okay, well, what about the capacity? Like do you have -- how much -- how many megawatts do you have that you could sign right now? And then it also has the balancing that you just described of, okay, how much of are we willing to do with our business model of not having a 5-year bare metal offtake with an investment-grade kind of counterpart. And so we're -- we look at our customers and their credit profiles and their growth trajectories and their funding and we allocate capacity to try to optimize in that. And so I'd say we're in a more nuanced game because we're investing ahead of the security of the committed revenue where a lot of our peers in the -- that are approaching it more from a neo cloud, bare metal side, they tend to have a customers and then secure the -- like that -- then gives them -- the finance and gives them the data center kind of financing, et cetera.

Yes. No, that's a great point. You mentioned on the cost side, we like that it's not about just maybe just availability, it's the cost of sort of bringing up this capacity and in the past, you have spoken about $20 million to $25 million per megawatt from a cost standpoint. The market has been very inflationary in terms of all these components, including now CPUs and memory obviously has been ongoing for a while. So as you think about putting that all together, what do you think about the incremental cost. Is that still the right range and it's the high end of that range? Or are we sort of talking about a big step up in sort of the cost to bring this up?

Yes. It's -- the $20 million to $25 million per megawatt in CapEx that we talked about was for the 31 megawatts that we were turning on this year. And again, you can see that. And if you look at our first quarter results, we added about $144 million of equipment finance obligations, and that was associated with the first 6 megawatts. So it puts you right in that range that we talked about. As you pointed out, the costs are higher now. And they're higher on 2 dimensions. One dimension is just component cost. So the cost of storage or memory is the primary driver, but even storage, like NVMe drives or -- I'm probably missing a letter in there, are a lot more expensive than they were. And so you're starting to see component costs across GPU and CPU go up. But the -- I'd say the bigger thing is actually the type of gear, the versions of the -- like some of the NVIDIA's latest technology that we're putting in, the B-300, you get more tokens per megawatt, it cost you more, but you get more tokens per megawatt. So the revenue potential is higher, which is good because that drives our $13 million in ARR per megawatt that will drive that up. But there is extra cost in there too, and so I'd say the good news with that is, well, it's everybody's got that cost and that's the cost in the industry. So at this point, we've been able to pass that on as just part of the pricing. And that's why I think you're seeing some of the prices of older generation also increasing just because it's -- you've got scarcity and you've got rise in cost structures, that's -- it's very difficult for industry investing this much to absorb that. It's got to be kind of passed on to the end customers.

What have you seen lately from your perspective on pricing in that regard?

Yes. I think you're seeing -- and this has been definitely a surprise for me, which is when we underwrote our investment in the 31 megawatts and even when we underwrote the investment in the 60 megawatts, we're projecting costs come down. I mean not that cost, prices come down, right? The older generation, you've got new generation technology, prices will come down. And so you got to be comfortable that you're underwriting a good business case even if that happens. Well, that hasn't been happening, right? The prices for H-100s and H-200s are increasing. And you've had a lot of people that -- Jensen and other folks, again, some of the folks at this conference talking about explicit increases in the and the pricing, we've seen that. And we're actually in a really interesting position in that because we don't have long-term contracts, we can rotate through a contract from 12 months ago comes up for renewal. We're not renewing that, could leave it close to what the price was before. We'll either increase the price, we'll move them off if they were a bare metal customer. We got a little bit of that left. We'll move them off. We won't even offer that to them and we'll move them to a higher grade level service or we can literally repurpose it and say, we're not going to sell it as GPU per hour. We're going to sell it as tokens and we can increase the monetization even then. So in general, the pricing for older generation technology is not only stabilized, it's increasing, which is -- it's a really good thing from a near-term perspective.

So purposely, you actually want a higher churn in some ways of where you price...

We're [ churning ]. We were talking about this in 1 of the sessions earlier today. Traditional SaaS metrics are really not super relevant right now. Like people ask you about NDR and when are you going to include AI and DR. I mean I don't know if we ever will. One, you got to be like 12, 13 months in before that actually makes sense. But if I rotate out a customer at a certain price, because maybe they were a marketplace. And at the time, we didn't have a go-to-market and so we're selling through a marketplace. And I said, "hey, we're not going to sell to you anymore. We're going to sell the cursor." And then if you looked at NDR, you'd say, "Oh, you had churn." Did I? Like I'm using the exact same equipment, I mean no gap in revenue with a better customer at a higher price. So it's just -- it's -- like you said, it's a different world and different metrics matter.

Yes. Interesting monetization opportunity that maybe doesn't get reflected in some of the metrics. As you think about these new capacity ramps, how should we be thinking about sort of the margin trajectory as well as you're bringing on this capacity? Clearly you had some pressure at gross levels, but can you just talk about sort of how we should be thinking around some of the puts and takes on margins?

Yes. No, it's a great point. The -- when you add data set capacity, it does 2 -- drives margins down, like point bars, it can get it around that. Why? Well, because as soon as you turn the data center lease on, you take lease expense. And because we pay for our equipment over time instead of largely. As soon as you take the delivery of that, the equipment finance depreciation-related expense hits right away. So your gross margin takes a pop, like right out of the gate, and then you grow into it with a -- as you fill up the capacity and you generate revenue. So it has near-term temporal margin kind of impacts. You also have -- as AI is growing, like it was, what was it, it was mid-teens percentage of our overall ARR, right, in the last quarter. As that becomes a bigger mix, well, the margins on the core cloud business are -- if you didn't have AI, they'd be in the 65-ish range, right. And you're weaving in margins that are not that high. They're not like 25% margins like you would get if you're just doing bare metal, but they're not 65. So you've got 2 things going on. You've got the merging of the mix shift of more AI that's got lower inherent margins, but then you got some temporal stuff every time you turn on data centers. But to me, the more important thing is to look at the aggregate margins when you include operating expense and you include everything else because the actual like resulting margins are pretty strong.

Yes. Maybe to touch on sort of what you announced at deploy, right? Like you spoke about the agentic stack that customers can now use. What's the adoption? I know it's very early days, right? But what are you looking at? What should investors be focused on in terms of across the several layers of the stack that you described, obviously, at the infrastructure layer like you have significant penetration. But as you go up the stack, how should we be thinking of the progression of some of those in terms of adoption rates? What are you anecdotally seeing, maybe if it's too early to sort of make a final judgment on where thing are?

Yes. I think like the simplest way to assess whether the strategy is working is to look at ARR per megawatt, right? Because it's like are we getting more value, higher layer services for the investments that we're making in capacity. So that's a simple metric. We also break down the -- within the AI customer revenue, how much of it is coming from each layer of the stack, right? So how much is being sold at bare metal, it's 19% now it's going to go down fast, and it -- like it's not only going down on a percentage, but on an absolute basis. We don't need to sell bare metal anymore. The inference layer will be where you'll see the most expansion like the fast because that's growing like crazy. And that's the products that you talked about that we launched that deploy the inference router and we're now selling for token, like we're selling serverless, where it's like people come in and like, hey, I want -- gibe me tokens," and "here's my latency in my throughput. Here's the price." And they don't even know what the infrastructure is. So that's like starting to really take off. And then a lot of the agent layer capabilities that we're selling, that's been really, really interesting. We're the -- I think the top deployment of Open Claw. We have like 70,000 active Open Claw like instances where there's -- things are happening so fast. There's a new 1 Hermes something that before we're 1 of the top in that. And so we're starting to see a lot of that. Those things are going to be hard for the market to see outside other than the anecdotes. But if you look at ARR per megawatt, and you see that continue to progress. And then as we -- we'll continue to disclose the mix of bare metal versus inference versus core cloud pull-through. And you'll see more core cloud pull-through, I think as well. I think those are the -- hey, is there really a differentiation here, and is this 5-layer software stack, is this real? Or is it marketing speak, and they're just talking about software. Everybody talks about software. If you talk about software and you get $9 million to $10 million in ARR per megawatt, you might have some really interesting software. It might be a differentiator, you're winning more bare metal than your fair share, but you're not getting higher layer services on top of it. And that's where I think the proof is in, okay, well, how are you monetizing that investment.

As you think about that getting customers into incremental layers, like where does that go from a $13 million per megawatt kind of range that you articulated currently to like where could that go when you think about using more and more pieces of the agentic stacks?

Yes. It's probably too early to say how far it could go. But what I could say is it's already going higher than 13. We underwrote the 60 megawatts at a higher ARR per megawatt than that. Part of it was because of the incremental token capacity as we talked about that we get from the higher CapEx that we're investing. But also we just launched a lot of those inference capabilities. We're getting now -- like I'll give you an example, when we won Character a while ago, we had -- we're unproven. We had to prove to them technologically that we could provide the service, and we had to demonstrate that it would save them 30% to 40% or improve their throughput by 30% to 40%. And so we got their inference workloads, but we didn't get any core cloud. And now when you're talking to cursor, they come with core cloud. They're, okay, we need this and we need NFS, and we need other stuff. And so our confidence in the core cloud pull-through is increasing. So we're definitely confident in our ability to drive that above 13 on an incremental basis, and we're seeing that in our -- in the customer wins that we're getting.

Okay. Well, here maybe -- look, the stacks had a phenomenal move, right? And I think it's reflecting sort of the enthusiasm around, a, the product offering, b, your execution and c, frankly, like your guidance has gone a lot like you've shown revenue acceleration, which is very, very meaningful going from mid-teens to now a pathway to 50%-plus. What do you think that are maybe some of the key risks that investors should watch out for, especially on the execution side? And anything else that you would point out?

Yes. I think if you think of the competitive dynamic, you've got kind of 3 different -- 4 different players. You've got the hyperscalers that are very, very focused on their own -- supplying their own capacity for their own internal use and on some of the frontier models. You've got the neo clouds that started with scale and capacity and are trying to layer on software because they see the same thing we do, which is inferencing is going to be a much bigger opportunity than training, and there's a lot of better characteristics of it because it's a production workload that runs, it's not episodic and it's harder to move, and it requires all these other things. So they're trying to add software capabilities. You've got inference wrappers that are taking advantage of, hey, it's really expensive. And so if I can optimize this, I can sell to people because I can save them money, but they don't own any infrastructure. They don't own GPUs. They don't own CPUs. They don't have any core cloud capabilities. So you think about all of those 4 players, and then you take us, where we started with software and we've got a very differentiated cloud where other than hyperscalers, the only 1 who has a CPU full cloud plus all the AI capabilities, but we don't have as much scale. And so it's a race, right? It's like everybody knows what they're missing. And the question is how quickly and how hard is it to fill that. So for us, it's like, okay, how do we add scale in a way that's still profitable and not overlevering ourselves, et cetera. For the other folks, they've got to worry about, okay, how do you actually build software if you've never run a cloud and your primary customers, 95% of them you actually don't even see their software. They just run it on your infrastructure. So that's a different challenge. And if you're a wrapper, you're like, I don't have any scale at all. I've got features and functions. And so what do I do? And so I think if you fast forward this in 2 or 3 years, the question will be, well, who won in that regard. And we like our chances of adding scale and growing from a capacity standpoint because we believe that running a production cloud both AI and core compute is pretty difficult. And there's only a handful, 3, maybe 4 other players, I'll call hyperscalers that do that.

Yes. No, I'd bet on your chances, too, because it just seems as though filling the gaps of the other places is a lot harder, and you already had customer evidence that has shown that if they were customers of some of these competitors, it was probably more economical and easier to move on to your platform and use the stack as a whole. So definitely excited about the opportunity here. Maybe to wrap over here since we only got a couple of minutes here, Matt. What should investors be most excited about as we look to the future over here? I mean, it feels like you've got this tremendous open-ended opportunity. So I would love to hear your parting thoughts on what investors should be most excited about?

I think that the thing that I'm most excited about, and I would hope that the investors would be excited about is, this is still such an early part of the growth trajectory of this market, right? There's clear evidence that there's going to be a massive amount of compute required, right? And I don't think anybody questions that. I think there's some questions around, okay, well, once there's a little bit more of an equilibrium and you don't have the scarcity, will there be commoditization and will there be people who got too far over their skis and are going to struggle. And when I look at what we're doing, it's like, well, what would you want to have? And when that happens, you would want to have highly differentiated services with more than just kind of a rental kind of a business. You would want to have customers that are embedded in your full stack of not just compute but storage and database where there's gravity, right, where there's really difficult to move that kind of -- those kind of workloads. And we're just kind of -- I think we're -- well, like you said, we've had a good run and the people are not paying attention to is, we're just getting started. There's like so much that we can do. And I think that we add some scale, we get some half, we'll be able to do some really exciting things.

Yes. Well, that's fantastic. In 23 years of doing this, I would say this is probably the BofA tech conference where the infrastructure bullishness that we've heard from across the board has been so consistent. And everyone thinks it's early days just because the demand is strong but the pipelines are exploding higher. So tremendous opportunity ahead of you. Great execution, and thanks for being here.

Great. Thanks a lot.

Thank you, Matt.

Thank you.

Thanks, everyone.