Y Combinator Startup Podcast
00:06:52 · Gustaf Alstromer, Chaz Englander
[00:06:52] S2: A year ago. So the models have probably progressed a lot in that year. What were things the models could do a year ago that were impressive, and what can they do today, and what are they gonna be able to do in the future? [00:07:01] S0: The whole industry or the industry we're in right now, really from January, is going straight line up. And I think the main difference that we've seen this year versus last year is last year was a year of testing, right? So everyone wanted to make sure they had some sort of exposure, as in they were trialing something or looking at something, but it was still testing, right? And us having ran consumer companies, we don't really care about revenue figures. We've always been obsessed with usage and retention. [00:07:30] S2: Right, right. That's good. That's good. The most valuable thing is want bring into B2B. Like, B2B people don't always know the most important stuff.
00:07:30 · Gustaf Alstromer, Chaz Englander, Arnie Englander
[00:07:30] S2: Right, right. That's good. That's good. The most valuable thing is want bring into B2B. Like, B2B people don't always know the most important stuff. [00:07:37] S0: Percent, which we think is madness. But this year, everyone kind of... The whole world went from testing to using. And there was a fundamental shift. Think these eugenics systems, there were small things like the improvement in things like function calling with some of the newer models, but everything has become considerably better by itself. And that's the interesting thing, right? It's like, I think, even if we do nothing, theoretically, our product will improve, which is a pretty interesting world to be right? And so when you're constantly working on something and you're pushing the boundaries, month to month what's possible just wasn't possible the previous month. [00:08:12] S1: I also think the vision models. I mean, when they first started coming out and improving, we were sitting next to each other. We were going crazy, weren't we? [00:08:21] S0: It was like the stuff that we [00:08:23] S1: could do with the vision models, if you think analysing files as an example, you know, OCR, okay, was amazing. You combine that with vision and its ability to read information from tables and charts, it really just changed the game.
00:08:23 · Arnie Englander, Chaz Englander, Gustaf Alstromer
[00:08:23] S1: could do with the vision models, if you think analysing files as an example, you know, OCR, okay, was amazing. You combine that with vision and its ability to read information from tables and charts, it really just changed the game. [00:08:37] S0: Yeah. And also, I think it's a misconception. So I think the industry still thinks that AI, or a large proportion of it, is kind of where it was even six months or so ago. We're seeing today is if you look at some of these data providers, they've got humans reading information from, say, public filings and putting that in structured format. The bulk of the work that we're doing and what we're seeing is models are already more accurate than humans in those sorts of tasks. And so I think that will take a little bit of time in terms of confidence, but I think some of the more lower level, more kind of data gathering and presenting type tasks are fully already being automated at the top firms. [00:09:17] S2: This is interesting. I'll tell you, at YC, the evolution went through at the same time. So two years ago, we would say, oh, you can't really sell the software to investment banks or private equity funds. They don't really buy software. Or if they do, they may buy one piece of software every ten years. The same was true for lawyers. But something happened last year. They all got very AI curious. [00:09:35] S0: They were [00:09:36] S2: curious about AI. They were like, let's do pilots to play with the software and try it out. And you were saying that this is the year when that turns into actual contracts.
00:09:36 · Gustaf Alstromer, Chaz Englander
[00:09:36] S2: curious about AI. They were like, let's do pilots to play with the software and try it out. And you were saying that this is the year when that turns into actual contracts. [00:09:43] S0: Exactly. [00:09:44] S2: And you can no longer say these companies don't buy software. That's wrong. They're all buying software now, and that's because this thing happened in the last twelve months. [00:09:51] S0: Exactly, and last year was the year of kind of proof of concepts. And now our average contracts are in the years, first of all. And I just think, in general, people are seeing a lot more shorter term or instant value. I also think, on the note of these firms historically, inclusive of law firms and others not buying software, that is, I think, true. I think the big difference here is this is like number one thing, from the very top, this is like the number one thing on everyone's agenda. So we are not selling the next CRM, or the next data vendor tool, or anything like that. We are selling what we're describing as the most advanced AI solution for financial services in the world, right? And I think if you are a CEO or an exec in general, you've kind of got to take that call. You know what I mean? And I think that's really played to the advantage for all startups, for sure. [00:10:43] S2: Can you describe some of these sales meetings? Like, who's the decider? Like, who decides to buy the software, and what are they like?
00:10:43 · Gustaf Alstromer, Chaz Englander
[00:10:43] S2: Can you describe some of these sales meetings? Like, who's the decider? Like, who decides to buy the software, and what are they like? [00:10:49] S0: CEO level or, in general, just the most senior people at the firm, regardless of if you are a top five or a top 10 investment bank, priority firm. I said, I'll sum them up, and whatever it might be. Which I think at the start, we found really strange, because we sort of thought that this would be looked at at a team or group level. It's really not. I think it's so important firm wide that everyone has to be involved from the very top. And actually, what we found is you've really got to get that buy in from the right person at the top, but then you've also got to get buy in from the people that are ultimately going to be implementing the tool. [00:11:30] S2: So you guys are flying to meet all these firms, where
00:11:30 · Gustaf Alstromer, Chaz Englander
[00:11:30] S2: So you guys are flying to meet all these firms, where [00:11:32] S0: Wherever they they are, wherever they are. So we have a bunch of people working out of Hong Kong and Singapore now. We've just opened a small office in India. About half of our overall team are based in London, and we have an office in New York. Again, I think it's clear the product is impactful, right? Because when we're demoing, we're laptop out. We're showing real use cases with real data, high use case frequency, right? So then if you think about why they wouldn't sign with you, a big part of that, I think, is trust and building that relationship. Because it's also a different dynamic. It's like a lot of times you're speaking to folks that if they make a wrong call here, they could get fired, right? And so you spend a lot of time building that trust. I think a big part of that trust is FaceTime and getting in front of people, obviously, but then spending the time the demo and how that's justified and really investing in things that are specific to the customer. [00:12:31] S2: I wanna go back a little bit to the two previous companies that you guys ran, Patlama and Fancy. Before we get into the details of what they were doing, what are some of the learnings you took from those companies into ModelML? [00:12:44] S0: I would say you've definitely got to enjoy it. You've got to enjoy building companies is my overarching thought. What about you?