The Exchanges

Q Mhm. Okay. Well, what makes this round different than other rounds?

A I think, you know, this round one, we really didn't need the capital. Uh, we raised it for pricing purposes, and we saw a couple interesting opportunities to accelerate R&D, particularly around AIR, which is our LLM native EMR platform, um, and our voice agent platform. And so the idea is if we can accelerate timeline, bring in a team of 40, 50 killer engineers to attack some of these problems that are adjacent, but converging upon the same solution set that we have in RCM and ambient, it's gonna be net better for our customers. Uh, number two, we've extensively used CBF, which is General Catalyst's non-dilutive customer value fund to fund our go-to-market expansion without needing to dilute shareholders. And so the last two years have been very non-dilutive for the company and for shareholders. And this was, you know, a pretty non-dilutive round as well against the valuation. We raised not a ton of capital because we didn't really need it, but it sets a new mark and it lets us sprint and continue building.

AI assessment note: “this round one, we really didn't need the capital. Uh, we raised it for pricing”

Q Kabir is building the AI powered OS for healthcare. Can you unpack that a little bit more and the state of healthcare?

A Yeah, I think that's a great question. So, Camura at its core is a software company that builds tools for providers and for healthcare administrators. This is a multi-trillion dollar problem, and even when you cohort it down, there's a trillion dollars spent on healthcare admin every year. That's clinical admin, that's financial admin, like revenue cycle management, um, all of the tasks that happen in the back office of a health system, like, Scheduling, prior auth appeals. We've built a series of fine-tuned language models and agents that automate all of those tasks and truly take a health system that might operate at two, three percent operating margin today because of all the labor needs and turn it into something that can operate at 20, 30% operating margin, like the top percentile healthcare practices and systems. And our belief is that that's not going to be a hundred different point solutions. That's actually actually going to be one revenue engine. Um, and a series of agents that are orchestrated on a single platform, which is ComirOS. And so for us, the, the, the next couple, I mean, you know, today a practice that uses our platform will use us for their scribing, their practice management, their documentation, their autonomous coding, their revenue cycle, and all of their back office needs, and see that boost in margin because they can grow without needing to have lab…

AI assessment note: “We've built a series of fine-tuned language models and agents that automate all of those tasks”

Q What is it like working with SUMA? It's a real hospital?

A It's a real hospital. It's a, it's a real hospital in Akron, Ohio, and you know, I, I gotta hand it to Hemant. The, the, the beauty of GC and I think Hemant is we are so ambitious, and they are not content being a VC firm that makes just great returns for LPs by investing in a Series A, And, you know, the two or three companies that matter every year getting into the rounds, they really want to bend the universe. And part of that means going to Akron, Ohio, buying a system that was on track to go bankrupt in, in the next couple of years and transforming it with AI. There are a lot of people that would be more than happy to, you know, sell tools to the miners and make a lot of money doing that. I think it takes a special person and a special organization to say, no, we're, we're actually going to go direct. And we're going to show the world that you can build a better hospital, and you can build a better health system, and you can do it today. You don't have to wait around and just make your money on software. Uh, we had RFK Jr. visit the hospital last week, and we, we hosted him there, and it was an amazing visit, showing him the transformation with ambient documentation on ComerStack, with ADOC, which is a, an imaging-based company that's essentially automating a lot of the scan process. Um, and, and so we, you know, one of the things that we've, we've noticed at SUMA is, The,…

AI assessment note: “It's a real hospital in Akron, Ohio, and you know, I, I gotta hand”

Q What's the biggest takeaway, lesson, or challenge that you've had through those processes?

A The, I think the number one learning in M&A is there's a lot of people that think M&A is about finding the perfect asset or acquiring the perfect asset and diligencing every, you know, making sure that it's pristine. Pristine assets are usually You know, there's no, there's no price disparity. There's no advantage that you can take of, of a, you know, of a pristine asset. Um, most M&A, and I think most good M&A, there are skeletons. There are things that you have to internalize that are not working in the company, and be okay with that because you have the other pieces that will make it work. You know, in the case of Augmedics, uh, great distribution, great legacy relationships, but the pace of innovation wasn't there, and they didn't have a software engineering team that was iterating every week. Uh, or in some cases every day, which is what you need in, in, in the age of LLMs. And when we brought that in, I mean, it just, it created so much value at HCA. It created so much value at Sutter. It's created so much value at our other, these other health system partners. Um, and, and so, but we have to be okay with the fact that it was suboptimal in some ways, and we were going to plug those things out and make a quick change. I'd say number two is you have to be very ruthless about stating what the culture of the combined business is. You can't, I think this idea of you acquire co…

AI assessment note: “the number one learning in M&A is there's a lot of people that think”

Q Uh, it's critical. So where does accuracy and reliability sit in decision making?

A Yeah. I, I think the, Where you see rollouts get completely stopped or companies go to zero overnight is in cases where, you know, a model or a tool hallucinates or performs, uh, incorrectly and ends up impacting patient care. And so, it ends up being maybe the most important thing. And the only way to truly ensure that is, one, great evals. You need to have a massive data set of historical, uh, uh, documentation or historic, whatever the task might be, coding, voice calls, To then measure your model iterations on, because when you release a new version of a model or a new version of an agent, it does some things amazing, but then it does a couple of things that are kind of weird, and there might be regression and performance deterioration on the fringes and in categories that you weren't even thinking about. And I think in smaller companies or in companies that don't have a lot of engineers, you can ship quick and get this stuff out, but that performance degradation goes unseen and then turns into cast like just cascading problems for organization later. So our, our belief is We work hand in hand, one book with the regulators, but I think more importantly with the customers to show them that the edge cases they care about always work in the test harnesses, always work in their back testing data, um, and then make that super public. And then at the same time, like when there ar…

AI assessment note: “And so, it ends up being maybe the most important thing.”

Q Because they, like, didn't they, wasn't this incubated with them or something? It was very early.

A So, exactly. Camero was incubated at GC, and Othellis, like, which, which is what I was running when I first met HT, um, you know, I was starting it right out of my Stanford dorm room at the time, and so I went to the GC office, which is on University Avenue, and I rolled up in my, I had a bike, and I rolled up, and the old General Catalyst office in Palo Alto was like, it was like a house, and then there was this, like, like, white picket fence, And he was, like, on the porch on a phone call, and I was like, where the fuck do I put my bike? There's no bike rack. Like, this is like, you know, we're in Palo Alto. Where are the bike racks? And so he's on the call, and I'm just like, I had no idea who he was. I was like, hey man, is it cool if I, like, walk my bike through this fence? And he was like, what? Like, who the fuck are you? And he was like, sure. And then he saw me walk in, and we had a meeting later. Um, but I think it just goes to show that the best investors are so plugged in that they're meeting With the random autistic kid on campus and giving them time of day when, you know, HT was, he was already running Livongo and he was already, you know, big and big time investor in Stripe. And the fact that he was giving me even like 20 minutes as a Stanford freshman just shows you, I think that's what it takes. I think, I think that was, to be great at anything, you have to…

AI assessment note: “So, exactly. Camero was incubated at GC”