A Product Market Fit Show | Startup Podcast for Founders
00:05:25 · Rafael Broshi
[00:05:25] S0: Sure, so our platform is a platform to build and deploy AI agents, in the customer experience space and back office space. Essentially, we take processes in large regulated organizations such as carriers, banks, and asset managers, and we help them automate those processes. In this case, that was a project in the customer experience space, where that carrier wanted to completely revamp their customer operations. That means that people that want policy servicing, that have questions about their policies, want to do some changes, get general information. That they'll be able to get information 24/7 accurately through AI, and because it is an insurance carrier, and highly regulated industry, there is no room for hallucinations. The quality has to be extremely, extremely high and there's a lot of things related to compliance and audit trail that you need to adhere to. So the POC was essentially take a very large corpus of public information, tens of thousands of pages from the website and other kind of sources. Take a mock API with personal information about a set of example customers, not real customers. Plus do a few, I'd say simple processes such as add a new driver to your insurance policy. So take all of those and then provide a chat interface for their team to try out your AI bot, AI agent, as if they were clients. And then, they have a set of thousands of different tests that I wanted to make sure that the more information you digest and the more information what we're seeing with those kind of AI tools. The more information and the more guidelines, and the more processes that you're trying to cover, the lower the quality of the responses. And that's what they wanted to check that there is no degradation because they already knew that the problem is not really figuring out what works in a POC if the POC is very, very short. Is that those kind of products don't scale in production and then things starts to break, and it's extremely, extremely hard to fix those mistakes. Because at some point, if you use a very simple architecture of one prompt, then the kind of context size causes the AI agent to hallucinate, to not be as accurate and it's very, very hard to fix. So that's what they wanted to figure out.
00:07:57 · Pablo Srugo
[00:07:57] S2: And what do you think you did? Maybe it's just technical, but is there a simple way of understanding what you did relative to the others? I mean, again, I'm asking you because in the respect of a founder selling enterprise, going through POCs, the odds that you're going up against others, very high, right? It's not like SMB sales, where it's just like, you go on a demo, they're like, oh, this is cool, I'll buy it. So you always got to think about where am I actually, you think your product is great or are you actually relative to the others. I don't know if you can share maybe some more details around that because that was the key piece, was that not just did you do it. You did it better than the others and then therefore you became kind of the number one choice.
00:08:31 · Rafael Broshi
[00:08:31] S0: So I think it all starts with the kind of point of view that we had when we started. So we actually started the company five years ago in the insurance space as a managing general agent. So we actually sold an insurance policy ourselves and started building a product internally to help us service our own policyholders. And then time went on, we closed the insurance product because we saw that the software we built internally to help us service our policyholder is more relevant. And because we came from a regulated space, from insurance, and we built the product to service ourselves. It was always more than a GPT wrapper that helps you answer FAQ. Because we were the one at stake here. It's not like you're selling a product and then you say, hey, good luck. I gave you the tool. You're going to be fine with it or not. It's that we were in charge of our own destiny. If someone would have sued us because our AI made a mistake, I'm the one who was supposed to handle that kind of lawsuit. So I think we build the product from an architectural standpoint a lot different, where when complexity increases it's not that we increase the prompt size. We increase the number of components of AI, components of LLMs that we use. So essentially when complexity increases, we increase compute, and we built things very, very differently in order to adhere to very accurate and very high standards in, production and complex environments. That's the main difference, very technical in that regard, but I think that's what won us the POC.
00:10:07 · Pablo Srugo
[00:10:07] S2: And maybe, last question before we kind of go to the story. I've met many startups who close one enterprise customer and it's easy to think when you close one enterprise customer, whether it's 100K or 500K. That, well, if you closed one, you've done the hard part. You just got to do this ten times, twenty, fifty times, whatever. You're on the road already, which is not the same again. With SMB, it's like, I've got ten customers. Doesn't really mean you're going to get to a hundred, a thousand, a hundred thousand, which is what you probably need. But with enterprise there's some of that, you know, logically, if you could get one, why can't you get ten? But oftentimes it just doesn't happen. You get the one and you kind of get stuck there. In your case, you're describing this POC, this moment as product market fit. Which entails that it wasn't just the fact that you got this contract, but it was going to lead to a lot more from a lot of others. Do you have a sense of what it was about this that gave you that feeling? That gave you a feeling that not only did we win $1 million contract, which is great, but that this signifies that we're going to win a lot other million dollar contracts?
00:11:03 · Rafael Broshi, Pablo Srugo
[00:11:03] S0: It's a great question and it really depends on why you won. A lot of companies that get stuck with one or two enterprise clients. It's because they're becoming sort of like their personal dev shop and essentially think about it. Every enterprise that decides to work with a small startup, whether it's ten people, twenty, fifty, a hundred, and there are five thousand, ten thousand people company. Why would they want to work with you, right? They want the speed and they want customization, right? They know that everything they're going to ask, you're going to execute and you're going to execute fast for them. So if you won the POC versus a large, let's say vendor. Because you customized everything about your system to fit what the client wanted, well, I'm not saying it's bad. Sometimes it's needed, but that should be kind of a yellow light in your head. [00:11:58] S2: That's a risk, yeah. That makes sense.
00:11:58 · Pablo Srugo, Rafael Broshi
[00:11:58] S2: That's a risk, yeah. That makes sense. [00:12:00] S0: That's a risk but if at the end of the day, you're saying, hey, I did not have to change anything. I just had to prepare the demo in the right way, or I just had to tweak, or I just had to do two integrations to meet their requirements. Then that's totally different and if at the end of the day what you hear from them are very, I'd say generic things that they were looking for, so this was not a POC of hey, you need to create an entire pipeline that connects to our policy admin system and then to our own internal CRM, and then to this, and then to that, something that is very, very unique. But it's we want something that responds fast, that takes a huge corpus of data, that has an audit trail, that is deployed on prem, which is something we do that others don't. If you hear those kind of generic things that people always tell you when you're starting to sell to enterprise, that it's not only about your features, it's the entire kind of holistic picture of how you deploy your services. So I think that's a pretty good green flag as to maybe you have something, although working with enterprise is a lot more than the product. The fact that you need to commit to SLAs, you need a team. This is not a small customer where you can say, oh yeah, we have a bug. We'll talk in two days, right? You're getting a phone call within four minutes from their SOC team. You have to deliver, otherwise there are penalties and it's not a joke, right? Winning an enterprise contract is the easiest part of working with an enterprise.