00:07:31 · Sebastian Johnson, Eric Landau
[00:07:31] S0: Do you think physical AI companies in this space or maybe physical AI data companies like yourself, can you get to the size and the scale of some of the LLM companies that we've got? [00:07:40] S1: Yes. The short answer is yes, and the, the data demand for physical AI will be as large, if not larger, than, for LMs, where LMs, we have the luxury of being able to scrape the Internet as the kind of precursor for a lot of the data. So, you can just go in and, have a smart web scraper taken and, take all of human written words or publicly available written words and use that to seed the model, but there's no equivalent of that for the physical world. So taking your entire life of all the experiences that you have and consolidate that across, you know, thousands of people and then giving that to a model, that dataset just doesn't exist. So a lot of these companies will be extremely data hungry to, get... Just get the models to the baseline level, which is equivalent to to LLMs, but they're still at an earlier stage than, like, what a GPT probably, like, two is. So we're still at the very, very early days of how these physical models will realize in in the real world. [00:08:38] S0: And they're collecting their own data for their own use cases. Right? We're not seeing this sort of, like, centralization of physical data yet, are we? We're not seeing, like, the open AIs, the data scraping on a huge multinational level. We're seeing it with individual companies scraping data for their own use cases. Right?
00:08:38 · Sebastian Johnson, Eric Landau
[00:08:38] S0: And they're collecting their own data for their own use cases. Right? We're not seeing this sort of, like, centralization of physical data yet, are we? We're not seeing, like, the open AIs, the data scraping on a huge multinational level. We're seeing it with individual companies scraping data for their own use cases. Right? [00:08:53] S1: Yeah. They're, they're using a number of strategies to to get the data that they need, but it's very Wild West and ad hoc now. The LM labs, they all had kind of a similar recipe of just getting the initial dataset that they needed to, bootstrap the model. Yeah. But a lot of the physical AI companies are, doing their own thing to get to the same place. And probably the ones that will be the most likely to win are the ones with the smartest data strategies because the model there, as of now at least, is is pretty commoditized on on that front. [00:09:24] S0: Interesting. And I wanna talk about this transition that you've gone from being, data annotation to this physical AI, much larger kind of infrastructure play. When we spoke that this was something you were betting on Yeah. Was this a bet that you made about the direction of AI, or was this being close to your customers being pulled in this direction?
00:09:24 · Sebastian Johnson, Eric Landau
[00:09:24] S0: Interesting. And I wanna talk about this transition that you've gone from being, data annotation to this physical AI, much larger kind of infrastructure play. When we spoke that this was something you were betting on Yeah. Was this a bet that you made about the direction of AI, or was this being close to your customers being pulled in this direction? [00:09:42] S1: I think those are, very, very correlated. So the, the choices that we make in the long run just come from being very close to the customers, talking them continuously, talking to people smarter than us in terms of, what kinds of, technological strategies are they looking at, what are they thinking about, and, you know, how are they kind of positioning themselves? And then consolidating all that and, like, you know, deciding, like, what parts of the product to build and, like, where to invest and go to market. So ultimately, term bets come from short term conversations. [00:10:13] S0: And talking about close to your customers, one of the things that we're seeing a lot of at the moment is sort of like FDEs or like forward deployed engineers. We're seeing this trend of like customer onboarding is kind of changing to be in like a technical field, especially where you have complicated products. Guess maybe yours isn't super complicated, but it's an AI product that maybe lots of people won't be naturally adept with. Are you adopting that model? Are you moving from a sort of customer success FTEs? Are you deploying FTEs in your kind of clients at the moment?
00:10:13 · Sebastian Johnson, Eric Landau
[00:10:13] S0: And talking about close to your customers, one of the things that we're seeing a lot of at the moment is sort of like FDEs or like forward deployed engineers. We're seeing this trend of like customer onboarding is kind of changing to be in like a technical field, especially where you have complicated products. Guess maybe yours isn't super complicated, but it's an AI product that maybe lots of people won't be naturally adept with. Are you adopting that model? Are you moving from a sort of customer success FTEs? Are you deploying FTEs in your kind of clients at the moment? [00:10:39] S1: Yeah. It's funny because we have spun up like an FTE team. And the kind of ratio that we see is, probably, like, you know, 90% of our customers just use the the normal platform as it is, kind of go through, like, the regular onboarding sessions. There's, a lot of complexity in a... In, you know, some specific use cases, a lot of them in in physical AI where, again, it's a wild west. No one really knows what's going on. And so you need someone on both sides of the, the customer relationship to, get to the right answer. And then also for customers that are maybe, earlier on in their AI adoption journey is like helping them, you know, take the right steps and, like, handholding them through through the process. So, yeah, we we are doing like a mixture of FDs and, like, kind of traditional customer success.
00:10:39 · Eric Landau, Sebastian Johnson
[00:10:39] S1: Yeah. It's funny because we have spun up like an FTE team. And the kind of ratio that we see is, probably, like, you know, 90% of our customers just use the the normal platform as it is, kind of go through, like, the regular onboarding sessions. There's, a lot of complexity in a... In, you know, some specific use cases, a lot of them in in physical AI where, again, it's a wild west. No one really knows what's going on. And so you need someone on both sides of the, the customer relationship to, get to the right answer. And then also for customers that are maybe, earlier on in their AI adoption journey is like helping them, you know, take the right steps and, like, handholding them through through the process. So, yeah, we we are doing like a mixture of FDs and, like, kind of traditional customer success. [00:11:28] S0: And when you talk about go to market more generally, how are you seeing that across the world? So you are... You... You're here in London. You seem to have a lot of customers, and I think an office out in San Francisco. Yeah. How's that split? Where are you seeing most of the the the revenue come from? [00:11:42] S1: Most mostly in The US. Yeah. We... And and most of the growth is now happening in The US. US is just the... You know, it's the biggest producer of AI now outside of outside of China. So you just have to be close to where your your customers are.
00:11:42 · Eric Landau, Sebastian Johnson
[00:11:42] S1: Most mostly in The US. Yeah. We... And and most of the growth is now happening in The US. US is just the... You know, it's the biggest producer of AI now outside of outside of China. So you just have to be close to where your your customers are. [00:11:56] S0: And as you've changed from the sort of data annotation play where, you know, Scale AI was the big sort of, like, competitor Yeah. Who do you see yourself going up against when you're kind of pitching to clients? We haven't seen [00:12:09] S1: many, like, full kind of comprehensive end to end solutions from the the data side. I... Not to say that they they don't exist, but we're we're just not seeing in a lot of the the deal cycles that we're doing. So, usually, when we have these types of conversations, it's, will that... The developer at the company try to, like, vibe code something themselves, or will they, you know, yeah. Go with us. [00:12:31] S0: Okay, Justine. So you are still filming in London, but you must be selling a lot in The US. Yes. And especially if you're now having, like, an FTE model, you must be hiring more people in The US. Yeah. Now that you've raised this money, how do you see the the balance between Europe and US changing in terms of your footprint?