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…y." So we we focused really intentionally on okay we're not going to be successful in trying to pitch these larger scale integration projects right now because we don't have enough volume to matter as we build that up then we will and then we will go do that and now that same carrier we are integrated with and like we've achieved that outcome. Okay. And so that was a big bit of what we focused on was what what is something that you can pull forward now and doing that in a way where that was commercial terms and we could do that pretty quickly. Okay. And this is a little bit of a different topic, but I wanted to ask you about this. We should we should include it in the fundraising section. Uh Rick told me that you fundraised without a deck. Is that is that true or that was that just the first round that you did? I mean, we I will say that we've never we have never run a formal process to date. And so, have have there been times that we put together a deck to like outline the business? Yeah, we did. We had to do a partners meeting with emergence and things like that. Okay. But we never in its traditional sense, I have a deck, I've got my data room, and like off we go. We we still to this day have not. We've been fortunate enough to grow the business and had early opportunities to build relationships with with investors who then like made a move, you know, to to invest in ThreeFlow. And so we have avoided that process in terms of running something that's formal and I'm going to run it for 12 weeks and I'm going to go through and meet with everyone. And um I think that's been advantageous for us in that it just it ejects you out of the business for some period of time. And obviously that's a reality for a lot of a lot of founders and a lot of companies. Um, but we've been able to again be fortunate enough to work with early, you know, Rick and and Joe, early stage sort of investors and their relationships with downstream investors also was really helpful. And that that allowed for us to start the conversations with companies before we were raising and just share with them the business and get them introduced to the business in a way where they were comfortable in that as an opportunity. And that then afforded us, you know, a way to then have the conversation around, you know, their participation, you know, on the cap table. And and so then what have some of the best hires that you made kind of look like? I think, you know, we were reflecting on this recently about like the composition of of who are the stars on the team. And I think there's there's this continuous pattern matching that that we see which is this combination of critical thinking and problem solving. Okay, that when we think about who's like whether it's in the EPD or which is our engineering and product design organization or it's our revenue org and you look at who are the star performers whether it's an IC, it's a line level manager, it's a director or it's an executive, it's those that have a world-class talent level of critical thinking and proactive problem solving sort of behaviors, emotions. Um, I was watching this interview with former President Obama and he had said those that have a world-class talent level of critical thinking and proactive problem solving sort of behaviors, emotions. Um, I was watching this interview with former President Obama and he had said something similar of like just just get stuff done. That's great. Yeah. Just get like and it it sounds so simple but it's so true of what you want just desperately is when someone's like I got it and you have confidence that they will take it and deliver the outcomes that you need. And it sounds like the most simple way. Of course that's true. But if you if you're really intentional about, you know, if I'm participating in an interview process, I spend a lot of my time trying to probe in for tell me about like tell me more about yourself and then giving me an opportunity to learn about times where they've that has shown up for them professionally. And if it's there, it jumps off the page because they've got all these different examples of how that's pulling them into these other projects. And it you can have someone who's really good at breaking down and like naming why this problem is a problem, but it has to be coupled with this like mindset of just moving proactively to solve a problem and not waiting to then get the permission or the direction of like how to go solve that problem. Because even at our stage, we're still figuring out a bunch of stuff as we're going into new segments. And what you want disproportionately is those that can solve for problems and also this idea of hiring for slope. Those that are just moving up and accelerating and growing at a disproportionately fast pace. And I'd rather have that individual who maybe doesn't have the same amount of experience but has the demonstration of the critical thinking, problem solving, and and the slope that over someone that maybe has a ton of experience on this particular area. And especially right now with, you know, the acceleration on the AI front, it's not like there's people that have all of this experience. People that are really good engineers are just like figuring this out on the fly. Yeah. Because they're interested in it. And so then that that breeds, you know, their ability to understand something and then leverage it, you know, to move even faster, which is super exciting. I think a big unlock for those that are trying to, you know, figure out what they want to do and what gives them joy in their own career is, you know, just finding those areas of solving problems and getting stuff done is so tremendously valuable. And part of again what we look for and part of when we look at who are the stars within our our team and our org, it's it's that you're like, "Oh, awesome. You just like took it." And so on with a lot of the AI stuff that you're doing, it's a lot of like ingestion and summarizing and like spinning the right information back. Like it's a lot of those types of problems with LMS that you're solving right now. Yeah, it's a lot. I mean, structuring document sets is like our really first core like use case. We do that across like quote proposal documents. We do that across policy documents. We're launching a medical product here mean, structuring document sets is like our really first core like use case. We do that across like quote proposal documents. We do that across policy documents. We're launching a medical product here soon and that's a big part of the unlock for us too. This is like health insurance. Health insurance. Yeah. The fully so previously we were supporting the self-funded medical and we're introducing this year uh fully insured medical for all market segments. And one of the things that we needed to do there was we had to figure out ways to process documents at at scale across um something called an SBC which is basically a review of coverage that you have on the health insurance side as well as a proposal document. There's actually like coordination between those two documents. Yeah. And so for us, leveraging not only the underlying foundational models that we're using, but also how we're building the vertical structures above it that allow for us to have very intentional cascading strategies around how are we breaking down the like the document sets so that we can actually focus the LLMs to have really high performance because we've cleared out all of the noise based off of our knowledge. And so a lot of the prompts engineering that the team has done allows for us to do that. And then also introduce things like a rag strategy on how we might refer to the current plan design because we need to move motions and we need to do workflows that relies on what is the current which of course a general foundational model is not going to have that information. And so leveraging both allows for us to at the end of the day just make it helpful and easy for the user because they they just want that. They just want it to work like magic. Yeah. They probably don't care what model you're using or like that it's even AI. Like they might be scared that it's this AI. In fact, that is that is the thing especially in a highly regulated space where sometimes that actually breeds more of like I'm going to talk about this kind of thing. They don't care. They just want it to work. They just want it to work in a way that they expect it. And because I was going to say like what's the the element then of like you're working at a like a startup. You're trying to take advantage of like the latest technology, but then there's also this like the most incumbent probably like legacy type of industry you could think of. like how do you combine them both together? Like what are the challenges there? I think you need to align incentives in the right way. And I think what what I've observed is most of the big insurance companies, the people there like have a desire. They want to move faster. They want to leverage it, but they have constraints because they have big tech that's old. And it's super easy for people to say like, "Oh, it's ridiculous. Like, you've got this old tech." But they're a $4 billion business that has acquired 19 insurance companies over the last 20 years. They might have like 19 different systems. 19 different systems. And so it's so it it's just such a copout in my opinion where people say like oh they're just like these old legacy incumbents…

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