Hello, welcome back to the Sifting Europe show. I'm Seb Johnson. Today we've got a banger, Erik, co-founder, CEO of Modal. How are you doing today?
Good. It's great to be here.
You're doing crazy things. The company is absolutely flying and I'm excited to get into some of those numbers. But before we do, can you maybe give a quick introduction to what you've built and I guess where you sit in the AI stack?
Yeah. So, I'm the CEO at a company called Modal. We build AI infrastructure, I think is the best way to put it, although we sometimes do other things too. We power a lot of inference and sandboxes and training and batch jobs and other things for a lot of customers like Cognition, Suno, Runway, Decagon, DoorDash and many others. The foundation is we built a platform, our own infrastructure platform, fairly general purpose. You can use it for a wide range of things but inference is one of the biggest use cases. We have a sandbox product as I just mentioned and yeah, been building it for about five years.
And how's it going? I mean, you raised a not small round earlier this year. I think it was $355 million.
Um, I think that's a total amount. It's, yeah, it's going super well. I mean, you know, AI is growing like, you know, so much demand in the space and I think we spent the last 5 years building a platform that, you know, there's just so much demand for helping all these new amazing AI applications, AI companies to build the applications of today and tomorrow. They all need infrastructure and we help them with that.
Yeah, it's amazing. And I think at the time you announced, was it $300 million of ARR, which was up 5x in about eight months or something, something like that.
Yeah. And it's a lot higher now. It keeps growing like very, very fast. So, you know, we were, you know, every month I keep thinking like it's got to, you know, it's got to slow down a little bit, right? Like, and then it just keeps going. It's been incredible.
And how do you forecast that level of growth? I'm sure this is true of so many AI companies today, but with the growth being unpredictably fast, is that a challenge to running the business?
It is challenging because we have to go out and procure GPUs a little bit ahead of time. It takes like 3 to 4 months to go out and do these commitments, sometimes 6 months. So it's a challenge, right? Like we, you know, straight line, you know, exponential forecast, we look three months out and project, you know, similar growth and we pray that that will keep happening. Usually what ends up happening is it grows even more than that. So so far we've, if anything, we've bought too little capacity but, you know, we're trying to be very aggressive with capacity right now.
And how does that, you know, how do you really, you know, when you talk about raising big rounds and giving yourself the money to buy these GPUs, how do you think about, I don't know, like running the capital, how much do you need to raise and when?
We don't own the GPUs, we rent GPUs, which is, you know, a little bit more capital efficient in the sense that we don't pay the full amount of the GPUs. We pay a little bit of money as a down payment often, we do these terms sometimes nothing. And so that has enabled us to be quite capital efficient. We also work with 20 different cloud vendors and that helps us get the best price out there. So we have capacity all over the world, different cloud vendors. I think we work with, you know, 100 different regions in total, maybe 150, Asia, Europe, US, some other places too. We got GPUs in every country almost. No, not quite, but a lot of countries. And so yeah, we, you know, like we do need money, like we're not a profitable company, but we've been actually very, very capital efficient and that's something I think is still quite important for us. We're a software company after all.
And where's that growth that you're seeing coming from in terms of both maybe region and type of user or customer?
It's, I mean it's primarily AI natives. So most of our customers are companies that have been started in the last five, seven years. I think, you know, generally that's true across, you know, all of these AI applications, there's just so much demand coming from these companies that fundamentally didn't exist before Gen AI because like, you know, Gen AI basically like, you know, created a whole business model. So a lot of startups and it's like kind of interesting because like I feel like the sort of conventional advice is always you got to go enterprise, that's where the money is, but like we don't see that, like the money is actually in like AI natives. We're starting to see a lot of digital natives waking up and spending a lot of money on this, like kind of rethinking their business models. I do think, you know, give it 5, 10 years, we're probably going to see the enterprise companies also ramping up their budgets but most of the stuff they're doing in AI today is frankly more POC type stuff. In terms of regions, I mean, you know, I'm European, you're European, you know, sadly most of the revenue today is coming from the US but we are actually investing a lot in Europe. We started a sales team in Europe very recently, just in the last few weeks, we're going to announce that very soon, very excited about that. We have an office in Sweden too. In terms of sectors and use cases, it's all over the place. I would say like a lot of generative media, like, you know, audio, video, music. There's a lot of like customer support type companies, a lot of coding models of course. And then we actually do a fair amount of stuff in computational biotech which is very exciting to me. So we have a bunch of customers using Modal for computational biotech and, you know, molecular simulations and all kinds of cool stuff.
It's interesting that you mentioned that most people say to go after enterprises, but it feels like in this age of Gen AI companies are scaling to enterprise size in like very little time, right? The old, it used to be, you know, go after enterprises because they're the ones with billions of revenue. Now you got companies, you know, that are doing billions of revenue in no time at all.
Yeah. Yeah. And so that kind of begs the question, what is even enterprise? Like I don't know, but like I think of it as like later, you know, later stage companies like again, you know, SAP and Bank of America, like probably not like our core audience right now but like might be in 10 years.
Do you think that says something more broadly about where the value of AI is going to really be captured?
I mean I think there's like two things going on. Like first of all there's like AI is like a very new technology and, you know, it's kind of clear that like startups will be better at like, you know, creating value out of that technology. And so I don't think it's super surprising that you see, you know, all these coding model companies or music generation companies, like these are fundamentally like completely new startups, right? Like predicated on AI as like fundamental business model, just like, you know, 10 years ago you saw people, you know, companies like predicated on like the iPhone and the cloud and like that was like the core thing. So I think there's a lot of that. The other thing is like I think the vendor stack is getting deeper too. Like we're building infrastructure. So in many cases we actually have enterprise revenue but indirectly because we sell to companies that then sell to enterprises.
Yeah, that's really interesting. So the companies themselves are not AI native. They're buying, they're paying for the services and the products that have been built by the AI native people who are then...
Exactly. Yeah. That's what I mean. The stack of vendors is kind of getting deeper in a certain way. So, and we're pretty far down in the layer. So, yeah.
Interesting. Okay. I mean, can you talk about some of the use cases and what you're seeing because I imagine where you sit, it's not just the location, the type of companies, but also some of the uses.
Yeah. I mean, some of our early customers was typically Gen AI. We initially saw product market fit in Gen AI around Stable Diffusion type use cases. So, image generation, video generation, music. Suno was an early customer, amazing company. They do AI generated music. Very cool. That was an area where we saw a lot of product market fit. Over time like I mentioned we've launched a sandbox product, seen a lot of success around that. So sandboxes basically means like there's a lot of LLMs generating code and, you know, you want to execute that code but you don't necessarily trust the LLMs. You don't want to execute on your computer, that can be dangerous. So we have a sandbox primitive that basically like encapsulates that code and lets you execute it in a safe way. And that turns out to be an extremely useful primitive for all the coding model companies. We work with, you know, companies like Cognition but also a lot of AI labs building coding models, background agents, work with some vibe coding platforms, seen a lot of success with that. We also do LLM inference of course, a very large, very important space. With the Chinese models and the open source models there's just so much demand especially now that they're becoming very, very good models. You see a lot of companies kind of switching away from the frontier labs to open source models, maybe fine-tuning, maybe using reinforcement learning, so that is a massive space for us. And then there's kind of a long tail of stuff like I mentioned, computational biotech is like a really interesting space. We work with a lot of robotics companies, sometimes controlling robotic arms. We work with some companies using Modal for weather simulation. So at its core I think Modal is like good for anything that's like computationally intensive, almost like HPC in a certain way. And then we have a lot of the primitives and you can build a lot of different things but the sort of commonality is like you need a lot of compute, typically a lot of GPUs.
The point you make around the Chinese open models is really interesting because it's something that we're seeing a lot on in like the, you know, the social media and people are talking about a lot. So it's interesting that you're seeing that. Like how significant is that switch from companies using the frontier models to more Chinese or open source?
Super significant. And I think it's like the sort of rationale has shifted. Like if you went back like a year ago, it wasn't necessarily that the open source models were as good, but the argument was like, well, if you fine-tune them for a specific domain, they can be almost as good and a lot cheaper. So, we saw a lot of demand for fine-tuning, like sort of, you know, post-training and reinforcement learning of those types of things. The crazy thing is like in the last few months like the models are basically as good like, you know, without any sort of fine-tuning. And so now you're seeing a lot of companies just wholesale shifting to open source models because they're cheaper. And so in a weird way actually like post-training I think it's been a little less sort of the topic of the day. I think it's going to come back. I mean fundamentally I think I believe in post-training but it's something, you know, relatively sophisticated customers do. And there's just so much demand for, you know, Kimi K2 and GLM 4.5 and Qwen 3 and all these models. Like these models are very good. They're Chinese, so there's a geopolitical maybe scary angle. But I also expect, you know, there's a lot of US labs working on new generation models. I think they're going to be almost as good, if not better than Chinese pretty soon. And, you know, hopefully Europe also has some models. I believe in the Western world. So I hope we can, you know, run open source models that, you know, may not have, you know, biases or who knows at some point.
And does this, do you see it really fundamentally presenting a risk to the frontier labs and their revenue growth because we're seeing this switch to, you know, open source Chinese models at the same time as we're seeing OpenAI and Anthropic's revenue skyrocket, right? We're seeing both things happen simultaneously it seems. Do you think it is a very serious risk to the longevity of, you know, the frontier labs or do you think both will win?
I think a little bit but I mean, you know, it's such a pie and the pie is growing so fast. Like I feel like, you know, it's easy to, you know, look at like sort of, you know, kind of, you know, fixed, you know, pie mentality, like, you know, what do you call a zero-sum, you know, fight. But in reality like you project 10 years down, I'm sure there's going to be way more consumption of open source models and way more consumption of proprietary models and way more like on-device stuff and way more like cloud stuff and way more all kinds of other stuff. So I don't know, I don't think we should necessarily frame it as like one versus the other. But of course if I was, you know, Sam or Dario, like I would look at these models and say like actually like they're pretty cheap and quite good, like what are they doing that we're not doing. And, you know, some people claim, you know, distillation, all these things and maybe there's some truth to it, maybe not, but like these labs are also very good, like they have very good people and it is quite remarkable that they've been able to build these models with a fraction of the research budget.
Yeah, I completely agree. Yeah, you're right. In 10 years time, the market size is just going to be 50 to 100x, right? If not more. Can we talk on the, you mentioned the kind of the European expansion, right? You're opening a new office here in London. You've got engineers out of Stockholm already. Why now?
Yeah. And I'm actually in the Stockholm office right now. We actually, I'm Swedish originally, but betrayed my home country and left to the US 15 years ago. But, you know, I come back every summer. It's an amazing country and I have a lot of connections here. So when we started hiring people, we hired a number of people in Stockholm and that so far that's been our only European presence. We have about 17 people here. By the end of the year we might be 30 people here. So Stockholm has always been for us like a very core engineering hub. A lot of very strategic projects. Our file system initially, now a lot of sandboxes have been driven out of here. Stockholm is very good for technology. I think for sales like what we found is like it's a little bit harder and so also Stockholm is not as big of a market. I mean there's some local companies but London is a much bigger market in Europe and, you know, has a little bit more of a history of, you know, technical sales. So now we're building up a sales office primarily. We're going to have some engineers there too over time. But we have already I think seven people in London up from zero in the last couple of months. So very bullish on London. I think there's a lot of incredible local businesses. Some of them are already customers. And I also think London is an exceptional base for sales into the rest of Europe. And, you know, I think Europe long term has the potential to be 20, 25, 30% of our revenue. Europe is a fantastic continent. There's so many different, you know, innovators, fantastic tech talent. I'm a big believer in Europe. So I think it's important for us. In fact, I actually think of it a little bit as like a first mover advantage. Like we as a company at Modal, given that we have a little bit of European roots, I think we have an opportunity to go very aggressively into Europe and, you know, take this continent and build something very large. So I'm very excited about that.
And how do you think about the overall go-to-market motion in Europe? You know, what has worked so well in America? Do you think it's going to be, do you think you're going to be able to translate that and use that same motion in Europe?
Probably not. I mean you should ask me in a year and see. I have certain assumptions, right? Like, you know, of course it's a different market. I have a feeling like, you know, what works in the US probably works like okay in the Nordics. I actually don't think sales is very different. Like they speak English, you know, and maybe the UK too. There's obviously a little bit more sort of focus on compliance and, you know, zero data retention and GDPR and types of stuff like that, but actually surprisingly little. And I think probably the reason is we're focusing so much on AI natives anyway. They tend to be not so compliance heavy. But I think, you know, when you start to look at like Germany and France and these countries, like my feeling is like, and this is an assumption to be clear, I don't know yet, but like you probably want like, you know, native speakers and you probably need a lot more like sort of focus on the compliance and, you know, you adapt to how to sell to local markets. We'll sort of see. So I actually think, you know, it's a little bit different. Nordics and the UK I think are more American markets is kind of my feeling. Germany and France maybe a little less. You have to have like kind of more of a unique approach there. We'll see.
Yeah, they get more traditionally like continental I guess. And how are you thinking about talent? You know, like who are you looking to recruit into the London office? You probably got some people there now, but like what's the characteristics or traits that you look for?
Yeah. Well, you know, you know Brits like they have this like extroverted sometimes like they're very gregarious. You know, we, I think that's a trait that does well with sales. They have an amazing accent. I, you know, I think all those traits are the things that we look for in our sales team. We've actually found a lot of really good sales people already from some great companies. So, you know, amazing talent so far. Then of course on the technology side I think we're going to hire a lot of people in London too. I think there's amazing AI talent. I think London is really the AI capital of Europe today. And so over time I actually hope that we can build up also local engineering talent too. I think Sweden has a lot of deep knowledge in systems, infrastructure, low-level like Linux stuff, but a little bit less on the sort of AI side. And I think London is like, that's where it really shines, like there's so much AI talent in London versus the other European capitals or the other European cities.
