The Exchanges

Q I mean, Jay, I go to my primary care, uh, doctor once a year, and they don't remember the stuff I told them 12 months ago. How do you sit on enough data to be able to tell the doctor, focus on these three things about Nathan, because we learned about these four years ago from this other data set we sit on?

A Yeah, well, so the thing that, you know, you've probably experienced this, um, something pops up for you, and you'll go to an urgent care setting. You might have a prescription filled from CVS. You might have it fulfilled from a local small pharmacy. You may then go see a doctor out of network, and you have a lab done, and so that data does not, is not consolidated in an easy format. We're able to sweep Uh, we, we identify like a geography based upon where you are, how many miles we're going to sweep all the care set settings that exist, pull that data in. We're really successful. We can capture, uh, incremental data by 90% of the patients that kind of run through our platform. But the challenge is when you get all that data, you better be really good at mining it because you can have thousands of pages of data. So we take that thousands of pages of data and we synthesize it down to the top two or three things. And if the doctor is curious and doesn't understand what we're suggesting, they can click in and go exactly to the precise spot in one of those records where we're drawing that conclusion.

AI assessment note: “We're able to sweep... pull that data in... synthesize it down”

Q What is an, I don't understand what that means in your space, what does an op mean?

A Uh, so our operations team, so when I talk about, you know, we have to capture information on behalf of a health plan, and, and look like, you know, from a standpoint of like our business, we're trying to disrupt a tech-enabled services model that's really heavy with people, and so our competition will Reach out with, um, they'll have people calling provider offices, a doctor to request a medical record to be sent in on a member. That information has to come in and be reviewed to make sure that it matches the member that they're seeking. They'll then attach it into the system, then it gets reviewed by a certified coder or abstractor. And we're trying to continually take out that layer of work and try to automate it. And so right now our team of our operations team Is about 50, and those are the 50 people who call on providers to get the record and review the record and attach it into the system.

AI assessment note: “those are the 50 people who call on providers to get the record”

Q Sweet. That's great. Okay. So that's the company. Now you, you mentioned this has been expanding over time. So take me back to day one. When'd you launch the company? What year?

A Yeah. So, uh, well, there's probably two day one. So I, I, I joined the company in 2016. I'm not the founder. I got, uh, hired by our investors to take a business that they had a lot of faith in, um, where they thought they needed somebody who had more scaling experience. So I jumped in and mid 16. And so there's kind of the chapter that's been written from 16 onward, but the company was actually launched back in 2009 more as a professional services business that started to morph into a software company. Uh, so the company's been around a while, but, but I like to think about kind of what's been happening over the last three years.

AI assessment note: “the company was actually launched back in 2009”

Q Yeah. This makes a lot of sense. Um, um, how did you make sure, I mean, do you have a history at other companies of doing M&A? Like how did you make sure to get that first one right? Are there any sort of a piece of advice you can give our audience consultants you use things like that?

A Um, I, I have done, um, M&A in the past. I wouldn't say, I mean, I've done, I was a seller. I sold a business. Uh, I was a part of buying, uh, two, three other companies in the past. So a number of experiences, but not, you know, not double digits. But I think what's most important is the product. You got to have product fit. You can't do it for financial engineering purposes. You go down that path. Uh, yeah, your numbers might look nice for a little while, but it's going to break down. Um, so, and, and we had to have the, um, the resources internally that could support the integration work. So the one thing we did, we brought, uh, a consulting firm in. To work with our team, to build the playbook with dynamic that we could use an acquisition to, and then whatever comes in the future, we, we expect to do more acquisitions, which is why we did that raise with Hercules that you noted. Um, but we built a playbook, um, to manage- Who did you, can I ask Jay who you used?

AI assessment note: “I have done, um, M&A in the past... we brought, uh, a consulting firm in.”

Q is they charge pretty substantial exit fees. They specifically charge Sisense. I want to make sure I get this right, right? A, a 2.55% exit fee on one deal, and then a, and then a 3.45% exit fee on their deal they did with Susie, another SaaS company. How did you think about exit fees? And was that a big deal? Was that a big deal negotiation point for you?

A Uh, it certainly was a big deal because we, um, we were thinking about what our, um, next financing step is and when a, another investor might enter. And if another investor entered in the, uh, near term horizon, would we pay that down? And what might that rate look like, uh, on a blended basis? So first off, like what was most important to us is that Total interest expense that we're going to pay with front end fees, back end fees, caring fees, and straight borrowing costs. That's number one. Yes, we were focused on the exit fee and, and, uh, we were able to lock in at a rate that we felt comfortable with. And, um, across the, the total borrowing, um, very healthy for the environment that we're in.

AI assessment note: “it certainly was a big deal because we, um, we were thinking about”

Q They had 38, about 30, 38 on the team when you bought it?

A Uh, yeah, probably actually a little smaller than that. Um, and, uh, and we, in the first 12 months of owning them, we sold more new business than they had sold in the prior five years. And the reason I call that out is because all of a sudden we were asking everybody to run a lot faster, to move a lot quicker, and how we were scanning up new customers, operationalizing it, Um, and for some, they weren't, you know, they weren't used to that. Some didn't really want to do that. We had some people who self-selected out, didn't want to move at that pace. Uh, we're really excited about the way the team has contributed and, and some of the, uh, the talent that has, has risen up. Um, but yeah, that wasn't for everybody. MD portals, the second acquisition, much more culturally aligned in the way we operate and the way we move. In fact, they probably have challenged us to move a little faster.

AI assessment note: “yeah, probably actually a little smaller than that.”

Q had 10% of the company right now. I mean, you're taking a two percent cut right on the, on the, on that dilution. I mean, there are so many ways you're doing about ten million a year right now in revenue total when you add your SaaS plus your professional services. Why not go use non-dilutive debts you save personally for yourself being self-interested? Do you save your two percent?

A Yeah. So we're, um, uh, it's a good question. Um, you know, I think the, uh, the two percent, um, The 20%, you know, haircut for me or for members of my team, I think we're willing to do that with the investor set we're bringing on, who, uh, we're bringing on a key investor that knows our space extremely well, um, and I think can play a significant role in how we scale. Uh, and then on the, you know, the topic of venture debt, um, we are, um, we do have venture debt. Um, we have, uh, A term loan, and we're also, um, we will have an AR line going forward, uh, to support the cash flow needs of the business.

AI assessment note: “we're willing to do that with the investor set we're bringing on”

Q a beautiful Excel model and they say, yeah, once the acquisition's done, we're going to cross sell and ARPU is going to expand and the teams are going to have no cultural issues at all. And the tech stacks are going to match. It's going to be perfect. How do you model an M&A process before doing it to try and de-risk the operational integration that has to happen afterwards?

A Yeah. Yeah. It's simple, right? Uh, like the Yeah. Uh, I mean, a couple of things for us. We, uh, our acquisition strategy is centered around identifying product that rounds out the solutions that we're offering today. So when we do that, we're effectively expanding what we can offer to the same buyer. So we're not asking our sales team to go learn kind of The buying pattern of a new executive inside of a health system that has nothing to do with the people that we're currently talking with. So that's kind of number one. Um, we did our first acquisition, acquired a more dated tech stack, and we took traditional kind of Uh, data center hosted, um, tech stack. We've migrated it to AWS and, and, uh, Which company was that?

AI assessment note: “our acquisition strategy is centered around identifying product that rounds out the solutions”