Bundled market data fixed connector failures

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 4:13

   So in that uptick of data for using codecs for financial applications, what sort of things did you learn that you then applied into the post-training of financial data? Yeah, it's a great question. I would say like, so yeah, I could talk a little bit about how we went about building Chachapiti for financial services. it was very unique. We haven't built a whole lot of first-party products. I would say Codex was really our biggest and main one. And it was the first time we developed a product where the product, the model harness, and the research was all kind of under one house and under one roof. And it really gives a lot of flexibility to go about building things. I think the biggest takeaway that I have from having worked on this for the last six months or so is in enterprise, you have to deal with the reality of the industry that you're in and go build around that.

2. 5:01

   And I think that piece is, it's easy to ignore. Like if you just think about it from first base principles, you can come to a conclusion that makes sense and you talk about it and you can defend it with, you know, with logic and reason. But if you ignore the state of the world that you're in when you start building and the forces that are at play within the industry to try, you know, it's either competitive forces, people have their own objectives.

3. 5:20

   And if you just don't think about that, you're not going to build the right product. Right. And so we saw that with Chachapiti for financial service and we thought about that a lot. I'll give you one example. Data. Data is like a huge part of how we thought about building the product. And, you know, and data was one of those things where on first principles, it was a little bit tough when I was talking about building this product to defend because, you know, you say, hey, like I want to go and bring quarter earnings transcripts into the product and bundle it.

4. 5:44

   And the first question that the first thing people are going to say is, look, there's an MCP connection in the store. Like, what is the incremental value that you're providing by bundling that in? On paper, it looks bad. It's like they might already have a license for it. so they might feel like they're paying twice for it. And they might have an MCP. And so, like, why are you building this? And the reality is we went and we tested all these MCPs.

5. 6:04

   And what we found was the error rates were really, really high. Some of the MCPs that we connected, some big names, 40% plus error rate on their MCPs, right? And so MCPs is one of those things where it looks great on paper, but you have to go look at the data and see what's actually going on. And so for data, we're like, hey, look, this is really bad. The only way we can go about fixing this at scale is to bring the data in-house, like just control that experience end to end. And the extra money that you pay on top to bundle that data is worth it.

6. 6:30

   So that was a product decision that we had to make that was very industry specific. And it's been resonating with customers. Customers love it. The number one thing they call out is the data. And so it worked. So you had good success in this. Tell us about the technical side of things for people building a harness