Nebius Group N.V. (NBIS) Earnings Call Transcript & Summary

Okay. Good morning everybody we got a packed house. Welcome to day 2 of the conference. Really pleased to have Nebius here, speaking with us. We got Arkady Volozh, who's the founder and CEO. I know there's been a lot of announcements and exciting news in your space, but Arkady,maybe for folks that are newer to the story, give us an overview, I think, of your background, which is also really interesting, but how you would position Nebius in kind of the AI landscape.

Nebius is a young start-up, a little bit more than 2 years old, not so young by experience. It was formed with several hundred of very well very well educated and experienced engineers with a very small 1 small data center, 10 megawatts and some pocket cash of $2.5 billion. That was our initial state. That's how we separated from our previous company. And we started this business in summer understanding that with our experience of building big infrastructure projects being a hyperscaler in the past. There is a new opening on the market, I will need a lot of infrastructure to be built. And we know how to do it, and there's not too many other people, teams who know how to do it, and there is a business to do. That's how we started $40 billion raised later, 5 gigawatts contracted later. We are now here company with real business, real revenues, engineers, products, sales marketing teams, what we're actually building is a small yet another hyperscaler we think what we are doing, there's not too many other teams again can do it. There's if you look around on the market. who builds all this infrastructure from the full stack from the ground, from the plot to data center to racks to software, cloud layer, application areas and so on. There's not too many companies in the world who do this full stack. We do everything just like again, we're not as big, but just like AWS, Azure GCP today.

Got it. And given there's a number of different players out there, hyperscalers, kind of more GPU infrastructure Neo clouds that primarily focused on providing capacity on the GPU side. Maybe let's dive a little bit deeper into the differentiation that you have that maybe puts you more in that camp versus kind of the bare metal GPU providers?

The infrastructure layer is actually it's main layers. So it's different players. There's people who build develop floods. They take plots, build electricity build shell and then leave these data centers to somebody else with profits. Then there's people who lease these data centers, bring active equipment on the site, GPUs, fracs, all these big systems, network connect altogether, and then they sell it to the next layer on, I guess, it's called bare metal. It's a basic infrastructure, almost not virtualized, basic actualization. And then people, bigger companies buy it usually the same hyperscalers and or big labs by this infrastructure and then run their product on this infrastructure and resell it to the next layer, which is application developers, corporate users, people who build applications to build AI applications, which then on the next level, generate ultimate value grains value to this world in different areas, generates new coding security, pharma, whatever, retail, generates a lot of value. And actually, in the food chain is the opposite. AI generates a lot of value in real life. It goes down to people who provide tools, they buy infrastructure capacity and capacity wise, the land and electricity, it goes waterfall. But it starts the generating value if AA stops generating value, all this is that. So far, it generates more and more value, and there's nobody knows when it stops.

You're on the road and phone, I'm sure you're talking with customers every day. Give us a sense of kind of the level of the demand environment right now, maybe compare and contrast that versus what you've seen in prior quarters? Like how would you describe it to this pactum.

So supply demand is a well-known problem now, and it's a good problem to have because demand exceeds supply significantly today. That's because I found a lot of niches to grow and to bring new value to generate value. And these initiatives are growing exponentially, whereas infrastructure supply is grounded in the real world, and it can't multiply this fast. You cannot make physical things 10x more a year of physical things. it's software, which you can multiply very quickly. So supply is scarce. Demand is growing and the situation at least for now, is getting, I don't know, worse or better. more and more severe. There is more and more demand. And unfortunately, with all this growth in infrastructure, it's not enough to cope with growing demand. So the difference is increasing. -- and it all reflects in prices in the whole this waterfall of pricing, prices going up -- go up and you can see it all-in expert management systems. Prices are going up in our business. we just reported last quarter that we started selling like everybody else, bar metal prices were at the level of $10, maybe $15 million per megawatt. We realize that demand is much higher. We tried many to adjust this pricing. And until we found the next level of $20, $25 million per megawatt for consumer level, retail level. And then on even shorter contracts. The demand is even more -- even higher and there is the people who need capacity now, not ready to wait until it's available in 2027, '28 and there is to pay much higher $40 million, $50 million at for this shorter-term contracts. And this is what we discovered, not only we as an industry, we as a company as well, discovered this year. we discovered that kind of manually, and we understood that on this disproportionate market when demand is high and supply is not enough. The best way to for prices covered to balance it through the price. You need some automated procedure to always balance growing demand versus limited supply. And we were among the first, I think, who went to develop the system of auctions. We first experimented. Again, it's why we were able to do it because in the past, we were -- the previous 20 years, we worked on consumer markets of Internet advertising or transportation services and all those industries, consumer industries, they're all balanced by some kind of auctioning systems both advertising, search pricing in over tax business in many, many areas. The balance is huge industries and the balances in those indices are all found in some kinds of auctioning systems. They're not just simple auctions. It's a very complicated systems, started simple and then eventually became very much complicated with a lot of people serving this area of price discovery. It's a separate business actually. And we think that probably something like this will start happening here in our industry, which is B2B. But still, price discovery should be determined by some kind of this auctioning system probably like with commodities or financial markets, every day, something trade stock, it's also kind of an auction system.

Yes. I thought the auction comments last quarter were really, really interesting and just sort of kind of revolutionary in this space. But how do you think I mean, you described this dynamic, a good problem to have, demandway more than supply and you're going to be bringing on a lot of capacity. You have you still have a lot of capacity to sell. You've talked about 5 gigawatts by 2030. How do you think about what makes most sense for Nebis in terms of the types of contracts you want to sign? Like for the next gigawatt of capacity, how much do you want to be auction, maybe short-term capacity through token factory versus multiyear committed deals. What makes most sense.

It's a question of optimization and derisking. Of course, it's great to put everything on short-term auction, try to sell everything at $50, $60 per megawatt. But then if something happens, then it happens, you have nothing we divide our customers in 3 big buckets. The main our main businesses in the middle market where we have let's say, mid-range customers, people who buy thousands and tens of thousands of GPUs for 1, 2, 3 years. This is our sweet spot, and this is our main market. We have dozens and hundreds of companies who there. And this is our target market. But to serve it, you need to have capacity to sell. So we had to start with a different sector. We started we became famous for our contacts with Meta and Microsoft, which is great contracts, great customers profitable and so on. But we basically had to do it. It's not our core business. We cannot sell. They don't need our software. They need just bare Metalic from everybody else. And there's many other companies who provide bare metal services new clouds. So we are 1 of many who serve this sector of the market. But we have to do it because we use those big contracts to help finance our main partner to build our independent partner cloud part. Now we have it built in the started building. It's just close to a gigawatt of capacity this year. And we want to build something like a gigawatt a year and then probably eventually more might half 2 gigawatt here to give you scale, the industry today builds, I don't know, 15, maybe it was 5 gigawatt A couple of years ago, it's now 10 probably this year, it will be 15, 20 gigawatt a year build in 2728. So we are probably a 5%, 10% market share in the world. It's a very small company. But this 5%, 10%, again, small in market share, but the industry is huge. And GPU cloud, like previous classical cloud is probably 10 large it's $1 trillion revenue business. So to be 10% of that, it's not bad for a startup.

Yes. Got it. Okay. And as we think about the execution of bringing gigawatts online potentially multiple gigawatts online per year down the road. There's been a lot of investor concerns around local oppositions, state mandates. What gives you confidence in the ability to navigate some of those complexities as you bring that type of capacity online.

To build on the ground to interact with a physical world is very challenging. And this is good actually, it is good for us. It means there's not too many people can do it, so it's we are kind of protected. There's not too many people who can build this kind of complex infrastructure in this scale. We can do it. We definitely face the same problems and sales challenges as the whole industry. This year, in U.S. specifically, this whole wave of people concerned with consequences of AI and data center build. It's a genuine concern. People are generally frightened they're friends of VI, the friended of this huge construction site in the neighborhood. Understandable. We experienced it just like everybody else in the industry, how we deal with it first of all, we diversify, we built not only in New Years, we built a lot in Europe. We billing think we are the largest builder in Europe, we built in the Middle East to be built in India in Japan now. through partnerships. It's not just 1 market. And when we build our own sites, actually, we do it from the beginning, we just recently realized that other people didn't do it here in the U.S. All the big constructions of the senses in the U.S., where under NDA is nobody guess who is building we always have come to decide openly like a developer company, I would say, build a boost where we show the project, we invite community, people to discuss what we're building. We have our educational programs for the communities. We employ local unions for to build it. We try to be open and friendly. But again, this is real life, real people, real concern. And specifically, this year, there is a lot of delays in the industry. Eventually, I think, again, it's not I don't believe that the situation will go so dramatically that the U.S. will start building data centers. If it happens, still will be built elsewhere maybe, but I don't believe it will happen. Somehow people will understand what it is. Actually, it's a huge, I think, data center is a very good industrial development for any community. First of all, it's much cleaner than anything else. Like in France, for example, we built we took a brownfield site in old factory, which used to produce tires, a bridge the factory, which produce tires. And now they have a clean, quiet data center, clean CO2 clean and no noise, and it's much bigger than having a factor in your background. So again, there is a lot of concerns, but I think maybe the industry should do better work explaining it. And it will be much more explanations. And but eventually, people, I think, will understand that it's good to have data centers which generate a lot of revenues for the communities

Yes. I wanted to shift to some of the headlines this week. There was a Palantir partnership that you announced and what stood out to me was in the press release, both you and CEO, Alex Karp, were quoted, talking about the partnership, which certainly implies a relationship from the top of the house down. So maybe talk to us about the evolution of that relationship? And specifically, what does this open up for you and potentially for them?

Where the synergy goes, we're building infrastructure, which we eventually need to build up to the customer level. The customers ultimately will be enterprises. That's where AI will be creating all this value. To get to the enterprises, you need channels. For us, it's just -- first of all, it's a great channel. They have a majority of their business is commercial and enterprises big commercial rates. For us, it's the way to get there. For them, they are proponents their customers big corporations, they are concerned that when they use the eye, they need to feed their data back to other companies. And the they lose they formulate is losing their severity. They kind of give up all of their secrets, data to somebody else, which then they incorporate in this universal models, which then later used by competitors to this kind of enterprises. So they would rather see a model which they can control and the infrastructure they know is they can look through to the ground and Pointer actually have chosen us because we provide this full stake infrastructure, which they we can have full control of they know what's going on up to the data center Rex, software, everything. On top of it, they put their software. Yes, we our level ends on the providing open models to that. Our talking factory provides all kinds of topnodels, open models, Chinese models, Demetra and others. They take the models. They have instrumentation Vontier has instruments for the enterprise, which allows them to take their data, take an open model. feed the data to the model. The model generates outcome. They use it as their new data, corporate data, which they generate. They feed it back to the model. And after several cycles, several cases in public cases showing that if you have 2 options, you can take very high level best on the market proprietary-modified something. And actually give up your data to them and use them, pay a lot or you can take an open model, train it with your data multiple times and after several cycles, you get the open model, which is generally weaker than the universal model. But after several cycles of training with your own data in your specific domain, it becomes higher quality than universal model. And that's what happened with Shopify. There was a famous tweet a week ago when they reached after 12 weeks, they reached quality. They started with Otovo, I think. And after several cycles, they reached the level of quality in their specific domain higher than GPT 56. So this cycle, open model and your own data in the cycle work helps to generate intelligence, which is smart narrow demand smarter than the Super Duper universal models. That's the thesis of volunteer. We fully supported and video support it. Probably, this is the way to go. One of the ways to go. Of course, Universal models will not disappear. They will have the place. But this is a thing which Palantir wants to do for this to do is they need to partner with open model and full step, which they can control and guarantee to their clients, that it's a verified stack. The data will stay there, and the quality is that's the partnership.