Commure: The AI Operating System for Healthcare

Tanay Tandon 0:00 I actually applied immediately. I got rejected, because I was in high school. [laughs]

Ankit Gupta 0:03 Yeah.

Tanay Tandon 0:03 And then I applied again, and I got rejected again. And then the third time, we came armed with a prototype-

Ankit Gupta 0:08 Nice

Tanay Tandon 0:08 ... that actually worked. The market is a great... I mean, it's just like punch in the face.

Ankit Gupta 0:12 Yes. [laughs]

Tanay Tandon 0:12 Like, it teaches you a lot, like, very quickly. I, I think our biggest learning is get in front of the customer, and then just solve problems for them. And, and start with one specific problem, regardless of how small it looks. We went from having no revenue to having $3 or $4 million in revenue in, like, a year. And it was like, "Well, we're done."

Ankit Gupta 0:29 Yeah.

Tanay Tandon 0:29 Like, we solved all the, all the problems-

Ankit Gupta 0:30 Yeah. [laughs]

Tanay Tandon 0:31 ... that are to solve. And then-

Ankit Gupta 0:31 Yeah

Tanay Tandon 0:32 ... and then you're like, "Well, no, actually, the game starts now."

Ankit Gupta 0:34 [upbeat music] I'm thrilled to be joined today by Tanay Tandon, the CEO of Athelas Commure. We're very excited to have him, because he's one of the leading providers of enterprise software to healthcare. Thanks so much for joining us.

Tanay Tandon 0:48 Thanks for having me.

Ankit Gupta 0:49 Why don't we kick things off? Why don't you tell me what Athelas is and what are you guys working on?

Tanay Tandon 0:53 Yeah. Uh, Athelas Commure builds software products for providers. And so we have tools that automate their day-to-day workflows, like Commure Scribe, which is an ambient documentation tool. Athelas Revenue Cycle, which is a payment stack. It's basically Stripe for healthcare and doctors. It submits their claims, uses LLMs to negotiate denials with insurance companies, appeal those denials, and then really render all of the data viz and business intelligence to run your practice from a financial standpoint. And then also a whole host of clinical tools, Commure Engage, which does back office and front office interactions with the patient, explaining their bills to them, uh, explaining what types of tasks they need to do to get prepared for a procedure like a colonoscopy, sending them appointment reminders. Do on the order of a couple billion dollars worth of payments volume every year. Um, help document, using our ambient AI tool, 20 million appointments every year, and then, uh, probably 150 million touch points, uh, annually on, on, on our patient engagement piece, um, spread in large health systems and private practices.

Ankit Gupta 1:56 And so this is sort of a bundle of pieces of software that are each solving kind of independent problems for a practice, and collectively sort of serve as the software operating system for this entire practice.

Tanay Tandon 2:05 That's right. And so, you know, our solutions are used by the physicians and the nurses in the practice or the hospital, and then also by the back office. So your accountants, your, uh, billing team, what we call revenue cycle in healthcare. Everything from, uh, you know, submitting the claim to actually, you know, ledgering everything up for the, uh, CFO's office.

Ankit Gupta 2:24 And you can actually do all of this with technology today. You can have an AI model that'll call up an insurance company and negotiate with them, and that actually works.

Tanay Tandon 2:30 100%. I mean, I think the ability for language models to both interact via voice and text with humans just got there a year ago. And so we're just at the precipice of what it can accomplish. Um, and when you walk into a health system, there are tens of thousands of people whose sole job it is to do these types of tasks. And if you can free up their time, you can bring that productivity back onto what matters the most, which is patient care.

Ankit Gupta 2:53 And I imagine a lot of those tasks are already outsourced to some degree. So you're kind of just slotting in to where they've already outsourced it to someone else.

Tanay Tandon 3:00 Exactly. They, they use vendors like R1, which is an offshoring RCM provider, Access, Omega. Many of them have their own in-house shops where they actually, you know, it's effectively outsourced, but they actually have the individuals on site. And the, the direction of the industry for the last 20 years has been offshoring. It works okay. For what it's worth, I mean, these became big businesses. But I think LLMs, there's an opportunity to reimagine all of that, where it's, it's pure software.

Ankit Gupta 3:24 And this ultimately becomes a product offering for all types of hospitals, both small and large.

Tanay Tandon 3:29 Yep. We work with the HCAs of the world, which is $100 billion hospital empire, you know, 3,000 sites of care, 186 hospitals, all the way down to your private practice owned by a single physician. And, you know, they use varying parts of the solution, but it's provided as one platform, which is revenue cycle, workflow automation, and patient engagement in one.

Ankit Gupta 3:50 What does that actually mean? Like, for someone who's not in healthcare, like, what do these roles actually look like in terms of where technology fits into them?

Tanay Tandon 3:56 Yeah. The, the way I think about it is the physician's day-to-day is really defined as interacting with a patient and treating that patient, uh, and then often generating the relevant documentation so that their back office, which is, think of it like their accounting team, their AR team, invoicing, can actually submit those claims to insurance.

Ankit Gupta 4:14 Yeah.

Tanay Tandon 4:15 One of the challenges in healthcare is the person paying for the, for, for the service is not the person receiving that service.

Ankit Gupta 4:21 So a person paying is like an insurance company or Medicare or whatever.

Tanay Tandon 4:23 Exactly.

Ankit Gupta 4:24 Person receiving it is the patient.

Tanay Tandon 4:25 Is the patient-

Ankit Gupta 4:25 Right

Tanay Tandon 4:25 ... themselves. And that individual, the beneficiary, you know, their incentives are to get treated, to get treated fast-

Ankit Gupta 4:31 Yeah

Tanay Tandon 4:31 ... to get the best treatment in the world. And often, the insurance company's incentive is to pay out as little as possible, and hopefully treat as little as possible, which is a counter-incentive to really what the patient is trying to accomplish.

Ankit Gupta 4:43 And so when it comes to then building technology, then you guys build technology for all parts of this, from the patient experience itself, as well as the kind of front and back office accounting and the kind of administration-

Tanay Tandon 4:53 Yep

Ankit Gupta 4:53 ... of that patient experience.

Tanay Tandon 4:54 We, we see it as, you know, there are two key protagonists in our story, which is the patients and the providers, and we build software solutions and hardware solutions for that group of individuals. And there's an effective enemy that's created as a result, which is the insurance company. And all of our tools are pointed at the payers in, in terms of trying to make their lives harder and make the lives of our customers easier.

Ankit Gupta 5:15 Okay. Very interesting. Okay. I wanna dive into your technology. But before that, I'd love to hear a little bit about the backstory of Athelas.

Tanay Tandon 5:20 Yeah.

Ankit Gupta 5:20 So why don't we rewind the clock, uh, to the very early days. Like, how did this company come about? Like, what was the very early days like? Um, what was your experience at YC like? And kind of how did you even begin to arrive at this idea that

Ankit Gupta 5:33 you're working on now?

Tanay Tandon 5:34 So I, I was very fortunate to have grown up in the Bay Area.

Ankit Gupta 5:36 Okay.

Tanay Tandon 5:36 And when you're in the Bay Area, Y Combinator is just in the ether. Like-People like Kasaar and Justin Kan and Sam Altman were, like, our heroes. And the ... I remember it was, like, 2013 or 2014 that we somehow snuck into YC Startup School because it was happening-

Ankit Gupta 5:52 Yeah

Tanay Tandon 5:52 ... in Cupertino. Uh-

Ankit Gupta 5:53 I think I was there too, actually. Also sort of-

Tanay Tandon 5:55 Yeah

Ankit Gupta 5:55 ... snuck into it.

Tanay Tandon 5:56 It was a great-

Ankit Gupta 5:56 Yeah. With-

Tanay Tandon 5:57 ... Startup School.

Ankit Gupta 5:57 Yeah, totally.

Tanay Tandon 5:57 I think Zuck came.

Ankit Gupta 5:58 Yep.

Tanay Tandon 5:58 Jack Dorsey was there.

Ankit Gupta 5:59 Yep. Yep. Same one.

Tanay Tandon 5:59 Um, Flexport did their interview on stage. And I remember I was, you know, I was, like, a teenager in high school, and I was just in awe of, of, of these people that had built such amazing technology.

Ankit Gupta 6:08 Yeah.

Tanay Tandon 6:08 And YC is this ecosystem that had enabled a lot of it, uh, and was starting to enable more and more of it. So y- you know, fast-forward a couple years, Y Combinator hosted this hackathon called YC Hacks. And, uh, I had read a couple papers about, uh, how you could use computer vision to potentially analyze blood cells and also use really cheap pieces of glass to enhance a smartphone camera to basically turn into a microscope.

Ankit Gupta 6:32 So this is, like, in 2016 or '17, something like that?

Tanay Tandon 6:33 This is 2014.

Ankit Gupta 6:34 2014.

Tanay Tandon 6:34 Yeah.

Ankit Gupta 6:34 Okay, cool.

Tanay Tandon 6:35 This was 2014.

Ankit Gupta 6:35 So this is, like, early computer vision. Like, d- deep learning is, like, just starting to happen to some degree.

Tanay Tandon 6:39 It's ... Yes.

Ankit Gupta 6:39 Computer vision's just barely starting to work.

Tanay Tandon 6:40 Like-

Ankit Gupta 6:41 Yeah

Tanay Tandon 6:41 ... the, the models that we were using them were, like, even, like, for, for computer vision were r- you know, you're using, like, segmentation algorithms like Watershed-

Ankit Gupta 6:48 Right

Tanay Tandon 6:48 ... and, like, you know, we ... Like Random Forest is what ... Like, were, like, the best models for, for often NLP and even in some tasks in computer vision. And so armed with those two pieces of information, I went to YC Hacks, um, and built this little really hacked together smartphone camera with a Random Forest that had been trained to classify malarial cells versus non-malarial cells, um, based off of a training set on the internet. And it worked, like, pretty well. Like you could-

Ankit Gupta 7:14 Yeah

Tanay Tandon 7:14 ... you could segment these two.

Ankit Gupta 7:15 Yeah.

Tanay Tandon 7:15 Um, and, and then, you know, I was a senior in high school at the time, but it became my science fair project that year.

Ankit Gupta 7:21 Nice.

Tanay Tandon 7:21 And I got very obsessed with this, this idea of, man, we can use computer vision to automate a task that someone like a pathologist, a very trained person, is doing in, in a, in a expensive laboratory and bring that care directly to the patient, um, and simplify the provider's life. And that eventually became Athelas, which was started as a med device diagnostics company.

Ankit Gupta 7:40 Oh, interesting. Okay. So when you, when you applied to YC then, so this is shortly after that, maybe a, a year or two after you were a freshman in college or something like that?

Tanay Tandon 7:47 So I actually applied immediately. I got rejected-

Ankit Gupta 7:49 Right

Tanay Tandon 7:49 ... because I was in high school. [laughs]

Ankit Gupta 7:50 Yeah, makes sense. [laughs]

Tanay Tandon 7:51 Um, and, and then I r- applied again, and I got rejected again. And then the third time we came armed with a prototype-

Ankit Gupta 7:57 Nice

Tanay Tandon 7:57 ... that actually worked. And it was after I'd spent about six months at Stanford, and, you know, the resources that you have access to with the med school and the, uh, uh, you know, and the, the mechanical engineering department. Like, we were able to put something pretty serious together.

Ankit Gupta 8:09 Yeah.

Tanay Tandon 8:10 Uh, and that's when we got in for Summer '16.

Ankit Gupta 8:12 And this was with a med device that was doing some type of kind of image-based analysis of-

Tanay Tandon 8:16 That's right

Ankit Gupta 8:17 ... uh, was it ... was the original idea of, like, blood sample analysis?

Tanay Tandon 8:19 That, that's right.

Ankit Gupta 8:20 Okay.

Tanay Tandon 8:20 So it was basically taking a small volume of blood, turning it into a monolayer so you could see b- you know, single cells basically like they're on a, on a smear. Um, and then basically a, a, um microscope with an imager attached to it, but was hacked in a way that it was very, uh, a large field of view and still high resolution. And then we trained computer vision algorithms to recognize and segment those various cells.

Ankit Gupta 8:40 And so at this point, you know, your background is primarily in computer science, I assume. You had some experience in this application area in biology in, in high school and early college. You know, what gave you the conviction to be like, "I'm gonna presumably drop out of college, start this company that is in a regulated industry with medical devices"? Like, how did you actually arrive at that conviction?

Tanay Tandon 9:00 I, I would say two key sources. One, my co-founder, Deepika, who's also one of my closest friends, uh, we used to compete in science fairs against each other, and her research was always way more, uh, uh, call it med device or bioengineering focused. And she worked through high school on this, uh, microfluidic test strip that could detect salmonella very quickly from, you know, produce. And, you know, I thought it was remarkable that you could build something like that in, in high school 'cause it was, you know, it was hardware, there was bio involved. You have to have a good understanding of, uh, y- you know, how these detection strips were actually fabbed and cut and whatnot. And so it was clear that, okay, we could build things in the real world with, uh, with microfluidics. And then number two, I think the ... Y- you know, when you're at Stanford, you get to meet these amazing professors. For me, uh, Chris Manning was, was someone who gave me my first shot in the Stanford AI lab under Richard Socher, um, who started Metamind, where I was a research intern as well. And I, I think they were just ... It was really motivating because for them it was like there's, there's no boundaries to what machine learning can do. You should go after these complex industries. Um, and they ... You know, Richard was ended up being the first check right after Y Combinator.

Ankit Gupta 10:08 Oh, cool.

Tanay Tandon 10:08 It was a 50K check. And, and I think that support really encouraged us as well.

Ankit Gupta 10:11 Yeah, totally. Okay. So, so let's now talk about your time in YC. You know, at this point it's just the two of you. Um, you're working on this regulated medical device. What did you set as kind of your demo day goal? And like, how did you ... What did you accomplish in those few months of YC that ultimately then put you on a trajectory to build something somewhat different now from what you describe now? And we'll kind of talk about that, that transition. But yeah, what, what did that first few months look like?

Tanay Tandon 10:33 I, I think the first week itself of YC was total shock because we came in with these traditional timelines for how long a med device should take or how long anything in healthcare should take.

Ankit Gupta 10:42 Which is, like, years or something.

Tanay Tandon 10:44 Years.

Ankit Gupta 10:44 Yeah.

Tanay Tandon 10:44 And, and that seemed pretty good to me. I was like, "Cool." Like, we're gonna be on this for a long time. It's, you know, we're gonna go super slow. I remember I had a conversation with, with, with Kasaar, who was our group partner and is also now on our board. Um, and he, you know, he, he, he was basically like ... He made me walk through every assumption on, why is that months? That, that just seems like it's like paperwork. You should be able to do it in a week. Why are you waiting for Stanford IRB to approve this trial where you could go to some local lab and probably get it done in a week?

Ankit Gupta 11:12 Right.

Tanay Tandon 11:12 Um, and I think because of that, Deep- can I sat down and just, like, reimagined how quickly you could build this stuff and, and really went from almost, like, zero-based budgeting but for a clinical trial.

Ankit Gupta 11:21 Right. Totally.

Tanay Tandon 11:22 And the other piece was, you know, if you're a competitive person, in our batch we had companies like ... Y- you know, Scale AI was in our batch. And, and this was a company that pivoted mid-batch and got to, like, millions in revenue by the end of the batch. You know, for us, we never wanted to just be the best healthcare company in the batch. We wanted to be the best company in the batch. And, [laughs] and so it was, it was this, this pressure that we sort of created for ourselves and the group partners created that really caused us to pace, uh, more aggressively than if we were doing it-Outside of, of, of, of YC.

Ankit Gupta 11:52 Yeah.

Tanay Tandon 11:52 And so we set this goal of we will finish a clinical trial and have a ready-to-go FDA submission by the end of YC.

Ankit Gupta 11:58 Wow.

Tanay Tandon 11:58 Um, and it was crazy, but we actually got the clinical trial done. We needed to redo some of the experiments per the FDA's request. And so the, the approval itself took a little longer, but we, we, we got the, the core basis of, of the, uh, clinicals done in those 10 weeks.

Ankit Gupta 12:11 I mean, that's pretty absurd pace, right? I mean, I think, like, when you think about a normal regulated medical device, we're talking about many years in that process. And yeah, I mean, I think this ability to kind of break down into its only ... What the critical components of it are, what parts you can actually shortcut versus not is, it's a very challenging head space to get into. And then you guys as, as 19-year-olds, I mean, I can only imagine some number of people who you talk to are like, "Who are these guys to be making a medical device?" Like, how do you go up against that? Like, w- how did you get yourself to not care, basically?

Tanay Tandon 12:39 We- we had many conversations where ... And we got a quote from Stanford where it was like, "We can run this trial and it'll be $120,000 and it will take three years."

Ankit Gupta 12:47 Right [laughs] .

Tanay Tandon 12:47 And, and I mean, when you see something like that, it's almost so absurd that it wills you into action a little bit, which is like, if this is the default system, I mean, something is broken. And, and, and I think, um, because of that, we thought to ourselves, "It's time to rethink first principles." And it really came down to, one, identifying a partner hospital that was small enough and willing to work with us very quickly.

Ankit Gupta 13:10 Mm.

Tanay Tandon 13:10 Uh, and that ended up being in Juarez, Mexico. So we flew out there mid-batch-

Ankit Gupta 13:14 Nice

Tanay Tandon 13:14 ... uh, ran the trial with them. Number two is really deleting as many parts as possible and running the simplest form of the trial. So instead of hiring traditional clinical trial operators, Deepka and I ran the trial ourselves. She took samples in the front room. I was in the back room running them on the device. Uh, and then we had a nurse that we had hired for the day who was running them on the traditional system called the Sysmex XE-5000. And we would then compare those results and show that they were accurate and, and equivalent to each other. Uh, and the whole process from finding the hospital to making sure the devices were ready to actually running the trial and then getting the results end to end was probably six weeks of the batch. Once we hit those milestones, that's when we raised our seed round.

Ankit Gupta 13:56 Okay, so what you started there, though, you started with this medical device. Today you're not a medical device company for the most part at least, or at all I think. What was that arc like? I'm sure there was many steps in which the company changed, but I mean, tell me a little bit about how you segment your brain into like the few eras of this company and how you-

Tanay Tandon 14:12 Yeah

Ankit Gupta 14:12 ... went from one of these to perhaps pivoting to a kind of another version of the company over the last few years.

Tanay Tandon 14:17 You know, we did YC. Uh, we raised our seed round from Sequoia, Alfred, um, over at Sequoia. And the next 18 to 24 months just became brutal focus on getting an FDA clearance. Um, get the device to a state where it can replicably run in, in, in clinical trials, uh, where you can, you know, all kinds of crazy tests. Like we have to drop the device and kick the device and, you know, things break and you have to be able to continue to pass the, the relevant tests. And that was it. We were laser focused on this one goal. And I think that was very freeing in some ways because it was the only thing we had to get done. We also only had $3 million to do it.

Ankit Gupta 14:52 Right.

Tanay Tandon 14:52 Um, and you know, the, the other piece of it was to start proving out the commercials. And that's when I started engaging with, uh, what became our first customer, which was actually a pharmaceutical company-

Ankit Gupta 15:03 Mm

Tanay Tandon 15:03 ... that manufactured a drug called Clozapine, which is a refractory schizophrenia treatment that causes neutropenia, white blood cell count reduction as a side effect. And you know, they told us, "We've been dreaming about a device like this." And, and they signed that first million-dollar contract even before we had approval just based off of the results of the clinical. So we had that commercial proof. We had early clinics that were adopting it and we were, you know, seeing them use it, and then we got the FDA clearance. And that was really the s- like the first like epoch of the company, the first like two, two and a half years. Once we got that, you know, the, the market is a great ... I mean, it's just like punch in the face.

Ankit Gupta 15:37 Yes [laughs] .

Tanay Tandon 15:37 Like it teaches you a lot, like very quickly.

Ankit Gupta 15:39 You must've felt like you were on cloud nine then. You were like, "Oh, we're, we're chilling. We've, we've figured this out now. Now we're gonna go to the moon with this."

Tanay Tandon 15:44 I, I mean, we got the clearance and it was like, well, we're done.

Ankit Gupta 15:48 Yeah.

Tanay Tandon 15:48 Like we solved all the, all the problems that are to solve.

Ankit Gupta 15:50 Yeah. Exactly. Yeah.

Tanay Tandon 15:50 And then, and then you're like, well, no, actually the game starts now.

Ankit Gupta 15:52 Right.

Tanay Tandon 15:52 And the exciting thing was that we went from having no revenue to having 3 or 4 million in revenue in like a year. So as far as traditional series A metrics and pacing, like we were there. The thing that we realized in parallel was, okay, we can probably scale this business to tens of millions in revenue and build a business that a Roche or an Abbott or someone will buy for, you know, 200 million bucks or-

Ankit Gupta 16:13 Yeah

Tanay Tandon 16:13 ... what- whatever that number is, like a good med device outcome. At the same time, we had this team that we felt could run through walls and had built machine learning software, had gone through regulatory, done the operations of device manufacturing, and we were in these clinics, like our devices were deployed, and we saw all kinds of problems.

Ankit Gupta 16:30 Hm. So you got in there by deploying the devices. You were solving all sorts of other problems they were facing, and along the way you discovered there's this massive other set of problems that you can solve too.

Tanay Tandon 16:38 Yep.

Tanay Tandon 16:39 We, we wanted to go from making their lives easier for a percent of their patients who we were serving with our Athelas One device to 100% of their patients, uh, and their whole chronic care panel with, you know, the telehealth tools and the revenue cycle tools. And, and I think, you know, my looking back, the, the reason this time period was so valuable is we would not have had, you know, a value giving relationship with these customers had it not been for the device. They trusted us.

Ankit Gupta 17:03 Right.

Tanay Tandon 17:03 They saw us as more than just a device company. They saw us as those kids that would show up in their office, set up the device, train them how to use it. And because of that, they would tell us about all these other problems they had in their clinics. Like, "Hey, when I get the result from the device, I have to upload it into this portal manually, and then I have to call up a pharmacist and tell them like, 'Hey, the fax is coming through.'" We would just hear these, you know, these complaints like, "Well, it would be amazing if I could, you know, upload this automatically or if I could fill this claim form out automatically to get the next set of medication adjudicated." And that's when we started building software and it honestly felt like playing on easy mode after two years [laughs] of building, building hardware and dealing with the FDA.

Ankit Gupta 17:41 You know, at some point presumably the software starts to take off and become a pretty significant part of your business. At, at some point do you ... You know, what is that process like of leaning in on that and perhaps, you know, abandoning the thing that, or, or at least leaning out of the thing that has been your initial driver that got you there in the first place that has this big pharma deal, for example.

Tanay Tandon 18:00 Yeah.

Ankit Gupta 18:00 What does that process look like?

Tanay Tandon 18:01 It, it was interesting because we had two paths in front of us. Be the best Athelas One medical device company in the world and just, you know-Build a great compounding 40 50% annualized grower in that, in that segment. Alternatively, it was bet on yourself again and expand the TAM and do more for these customers, um, based on the learnings we were getting from the market.

Ankit Gupta 18:22 And also, when was this, by the way?

Tanay Tandon 18:23 This was in 2020. Um-

Ankit Gupta 18:25 So you've been at this now for, like, four-ish years. Like-

Tanay Tandon 18:28 Yes

Ankit Gupta 18:28 ... this has been your thing. You're a med device company. You're growing this thing.

Tanay Tandon 18:31 Yes.

Ankit Gupta 18:31 Now, 2020 is coming, a lot of things are happening in the world, uh, as I'm sure is gonna be relevant here.

Tanay Tandon 18:36 Yeah.

Ankit Gupta 18:36 And then also you're starting to see that there's an interesting new opportunity in software.

Tanay Tandon 18:40 Yep. And I remember it was, I, I forget, was, it might have been Robinhood or it might have been some company. We, we had this interesting, uh, uh, fireside that we went to, and they talked a lot about share of wallet and this concept of you wanna do more and more for your consumer and go from just being, you know, with Robinhood, like their toy stock, couple hundred bucks playing around, to like, "No, this is like a meaningful financial product for your entire portfolio." For us, the na- the analogy was, w- was apt because we want- we, we wanted to go from treating 1% of their patients, these refractory schizophrenia patients that were treatment resistant, to treating all their patients. And I remember Deep, my co-founder, she was in one of these clinics. She spent a lot of time in these clinics, and she was like, "It's insane. We are helping them for 1% of their patients, and they love us so much. Imagine if we could br- build tools for all of their patients, their 4,000 patient panel." And, and I think that's when we took the bet, where like we can build a multi-billion dollar software business, sensor business in this segment by expanding what we do for these customers and, and, and grow a lot faster than the 100,000 total patients that had this one condition.

Ankit Gupta 19:43 And then this was before the LLM era was really taking off. You were obviously a machine learning company, and you had a lot of experience with building software. Um, but like what did that initial software look like? Like, what types of problems could you solve then? Presumably now you can solve many more.

Tanay Tandon 19:55 Yeah. We started with the basics, which is one, uh, COVID hit, and, and as a result, our providers needed ways to monitor their patients in their homes. So we built a basic telehealth portal and a set of remote monitoring devices that connected into it and allowed them to inter- interact with those patients, many of whom also use the Athelas One device in the point of care or in their homes. The very next thing we started playing around with was workflow automation as it related to claim submission and payments. So everything from collecting dollars from these patients to, uh, you know, starting to submit claims to insurance. And first we did it just for our, you know, this subset of remote monitoring and clozapine patients, and then expanded organically to more and more of the practice.

Ankit Gupta 20:39 And, and these are problems you basically discovered from being in their offices.

Tanay Tandon 20:42 Yes.

Ankit Gupta 20:42 Like you and your co-founder are in there, and you're noticing and hearing from them about whatever other problems they're facing, and you're kind of seeing, okay, like as exciting as this is, we sort of have to solve these as we go.

Tanay Tandon 20:51 E- exactly. There is no other way to discover these problems than being in your customer's day-to-day and, and, and just seeing them because there's so much nuance to where they get stuck.

Ankit Gupta 21:01 Yeah.

Tanay Tandon 21:01 And it's not something you can derive, you know, by reading an article or, you know, watching a video online. You, you have to be in the, in the heat of things.

Ankit Gupta 21:08 Yeah, totally. I mean, I think we see this with, with companies every day today, especially in this sort of new technological moment, is that it's very hard to conceive of great startup ideas kind of in your home or in a lab. It's much more likely to encounter them somewhere-

Tanay Tandon 21:19 Yes

Ankit Gupta 21:19 ... in the field by being in there. And so for you guys, that sort of was a, was a game changer in putting you in that place.

Tanay Tandon 21:24 100%.

Ankit Gupta 21:24 Well, okay. Well, why don't we, you know, kind of move forward now a little bit to, to today and, and I can get there by kind of talking about what the last few years has looked like in healthcare generally. I mean-

Tanay Tandon 21:34 Yeah

Ankit Gupta 21:34 ... there's been an incredible amount of changes happening in healthcare. To your point, there's these massive mega conglomerate style hospital businesses. There's consolidation in payers and PBMs. For you guys, as you see this sort of changing landscape, where do you-- one, where do you fit into that landscape? And then also, how does that changing landscape affect your business and as you think about growing it?

Tanay Tandon 21:54 I, I think it's, it's re- it's really interesting 'cause if you go back to the '90s, uh, the life of a physician was great. They had a tight panel of patients. They knew them personally. They treated them, and if there was, you know, chronic diseases, they were able to talk to the patient very quickly. Idea of a concierge doctor was, was fairly common. You know, anyone in upper mid- middle class had a concierge doctor of some kind. And as the bloat that came from insurance and regulation and, and, and just what we turned healthcare into and this sort of like admin state-

Ankit Gupta 22:25 Yeah

Tanay Tandon 22:26 ... is what really broke down the productivity of a physician, where they turn into these, these, you know, cogs in this greater wheel, and there's, you know, patient productivity numbers they have to hit. There's countless tasks they have to do. Regardless of how efficient they are, they always take documentation home, and they're filling out paperwork. And I see it as this great misuse of, of talent in that we have some of the most intelligent, well-trained, uh, uh, well-intentioned people in the country spending their time doing tasks that really software should be doing for them, uh, LLMs or not. And what we've seen happen is a lot of physicians give up on this dream of the private practice or the physician-owned practice in change for joining a large health system that does take on a lot of the overhead that you now need to pay in order to just operate a health system.

Ankit Gupta 23:14 This is like negotiating with insurance companies and with PBMs and having, uh, pharma relationships and all that kind of stuff.

Tanay Tandon 23:20 Yep. Paying for an EMR-

Ankit Gupta 23:21 Yeah

Tanay Tandon 23:21 ... dealing with malpractice. And so all of this made it harder to practice care-

Ankit Gupta 23:27 Yeah

Tanay Tandon 23:27 ... and, and, and turned it more into this, this, again, like this admin business. And, and I think now with LLMs, there's this generational opportunity to free the physician and, and really bring them back to what they love doing the most, which is rendering care. And I think our work is in service of that. Uh, take the work tax and just nuke it. Take every part of their revenue cycle, their back office, their documentation, um, and, and use software to automate, uh, large chunks of that.

Ankit Gupta 23:53 And I mean, you guys sell to, you know, both this mid-market and larger market or, or any kind of enterprise market. It feels like what you're saying here is that this mid-market is what you see as potentially best suited to take advantage of, of LLMs and especially sort of this broader technological adoption because it frees them from needing to consolidate into these bigger enterprises. And perhaps the advantage of the bigger enterprises won't be as much the case in the future. Is that kind of how you see it, or do you think not so much?

Tanay Tandon 24:21 I, I, I think it goes both ways. One, I think we will see-- it's sort of the analogy we use is like Amazon and Shopify, where-Over the last 20 years or 10 years or whatever time period, Amazon has grown remarkably, um, as it's, you know, taken a lot of share from traditional retail and also expanded what we order online. But then Shopify has exploded as well as more people are able to start their own businesses. And I think you will have this aspect of the physician who practices in a health system, but then also has their own practice-

Ankit Gupta 24:50 Right

Tanay Tandon 24:50 ... um, and chooses their hours. And because of the fact that software is automating more and more of their day, they can see more patients and do it in, in a way that is sustainable and gives them energy as opposed to drains them out by the end of the day.

Ankit Gupta 25:03 Yeah. So let- let's talk about that a little bit in terms of software automating more and more of their day. There's been a lot of software adoption in healthcare over the last 10 years, most of it through electronic health records and, you know, kind of payment portals with insurance-

Tanay Tandon 25:14 Yeah

Ankit Gupta 25:14 ... and whatnot. Um, but a lot of it has been promised to doctors as saving them time or-

Tanay Tandon 25:20 Sure

Ankit Gupta 25:20 ... helping patients in various ways over the last decade. But the critique has often been that, well, it's not really been about that, it's been about getting paid for care, it's been about billing mostly-

Tanay Tandon 25:29 Yep

Ankit Gupta 25:29 ... and not actually about care. How do you see what that technological adoption story looks like over the last decade and then over this next decade?

Tanay Tandon 25:35 Yeah.

Ankit Gupta 25:35 Like, what are things you think are gonna be fundamentally different about this m- technological moment?

Tanay Tandon 25:38 I- it's, it's definitely true because a lot of the digitization and creation of EMRs came from a place of compliance and a place of, of, of billing and institutionalizing a lot of regulatory requirements as opposed to true, you know, un- un- unleashing the doctor. You know, Do- Dr. Klasco, who's one of our, uh, uh, you know, he used to run Thomas Jefferson University, the, the health system, um, you know, he calls this the epidemic, which is like there's just-

Ankit Gupta 26:04 Right

Tanay Tandon 26:04 ... this proliferation of, of work tax in every org in the country-

Ankit Gupta 26:08 Right

Tanay Tandon 26:08 ... in IT departments, in, you know, the physician's day-to-day, and it didn't solve the problem it set out to solve because the software was built from the perspective of the CIO's office and the CFO's office.

Ankit Gupta 26:18 Who are optimized around getting paid, basically.

Tanay Tandon 26:20 Exactly. We're optimized around getting paid and not getting sued.

Ankit Gupta 26:23 Yeah.

Tanay Tandon 26:23 And, and those are the, you know, the two, the two drivers. Uh, you know, the CLO's office as well. Now, I think you're seeing a lot of physician-driven adoption of these tools. One, post-COVID, we really stressed the system out. We, we burnt, we burnt out our physicians or burnt out our nurses, and there's almost no option but for them to use these tools-

Ankit Gupta 26:42 Right

Tanay Tandon 26:42 ... uh, uh, and, and, and push for the adoption of these tools in order to just keep up with their, with their day-to-day patient volumes. Our loudest advocates, even in the largest health systems, are physicians.

Ankit Gupta 26:52 This is really fascinating. Well, that feels like a huge difference, right? I imagine in selling the first version of EHRs five or six years ago, you're, yeah, largely selling to central IT teams-

Tanay Tandon 27:01 Yep

Ankit Gupta 27:01 ... CIOs, that type of thing. Here you're saying today when you approach selling your recent software, it's an individual doctor who's your advocate.

Tanay Tandon 27:08 100%. We, we have, we have a self-serve ambient documentation tool called-

Ankit Gupta 27:11 Yeah

Tanay Tandon 27:12 ... Commure Scribe. And-

Ankit Gupta 27:13 Yeah. How does that work actually?

Ankit Gupta 27:14 Can you tell us a bit about that?

Tanay Tandon 27:15 I would say it's one of the explosions in software categories recently. You've probably had... In terms of like really fast LLM adoption, I think you've had coding tools like the Windsurfs and the Cursors of the world, and then you ha- you've had ambient documentation tools, um, in the, in the healthcare world. And ambient documentation listens to the conversation that a patient and a physician have, it summarizes that, and then it generates all of the documentation based on being trained on previous approvals, previous pieces-

Ankit Gupta 27:39 Right

Tanay Tandon 27:39 ... of documentation, and basically hands it off to the revenue cycle teams ready to go. Yeah.

Ankit Gupta 27:43 It's like a perfect problem for LLMs.

Tanay Tandon 27:45 It's-

Ankit Gupta 27:45 Those things, LLMs would be really good at.

Tanay Tandon 27:45 It's a perfect problem for LLMs.

Ankit Gupta 27:47 Yeah.

Tanay Tandon 27:47 You have transcription, you have summarization, you have, you know, references and citations back to clinical source material all in this one, you know, or one set of models. Uh, and that tool, we went from 2023 doing maybe 100,000 appointments through that tool, to this year we'll probably do 20 to 25 million appointments through that tool. There's a self-serve motion that has gone from last year zero appointments to this year 5 million appointments. Um-

Ankit Gupta 28:13 Self-serve motion as in you don't go through the hospital IT team at all?

Tanay Tandon 28:15 It's a physician finds it online, uh, we advertise directly to them, they sign up often paying with their own credit card.

Ankit Gupta 28:21 Wow.

Tanay Tandon 28:21 Um, from-

Ankit Gupta 28:22 That seems new.

Tanay Tandon 28:23 It seems crazy. I mean, I was shocked.

Ankit Gupta 28:24 Yeah.

Tanay Tandon 28:25 When, when we saw this working, uh, it was... You- this is not behavior you've seen in healthcare before.

Ankit Gupta 28:30 Yeah.

Tanay Tandon 28:30 And from that, we, you know, we then go upsell almost like Slack or Dropbox or one of these traditional software tools-

Ankit Gupta 28:37 Yeah

Tanay Tandon 28:37 ... the whole enterprise, where we pitch the integrations into their EMR, the whole workflow tool. Um, and that's been a massive, you know, source of, of, of expansion for us.

Ankit Gupta 28:47 If I'm a founder, you know, I, I might be thinking, "Well, isn't it gonna be really annoying in terms of HIPAA and in terms of all these rules and whatnot-"

Tanay Tandon 28:53 Yeah.

Ankit Gupta 28:53 "... in terms of actually getting a doctor to sign up?" Like, it's not even intuitive to me that a doctor is allowed to self sign up for, for this type of thing. How do you guys think about that? Is that... Has something changed that makes it easier or was it never actually as hard as people thought?

Tanay Tandon 29:05 It, it's a good question. I think there's definitely a lot of compliance departments in hospitals that are, are very much against self-adopted software. But the productivity gains are so, so great that it's happening one way or another.

Ankit Gupta 29:16 Yeah.

Tanay Tandon 29:16 Um, and the options that a compliance department at a hospital has is either, you know, sign up and make this part of the institution, or-

Ankit Gupta 29:25 Right

Tanay Tandon 29:25 ... you know, tell your physicians to continue being burnt out, and usually they're picking the one that then ends up with happier physicians. You know, there are totally ways for there to be HIPAA compliant self-serve tools.

Ankit Gupta 29:36 Yeah.

Tanay Tandon 29:36 Now, that might defy the individual policies of a, of a private institution like a, like a hospital itself, but from a pure HIPAA compliance standpoint-

Ankit Gupta 29:43 Oh, right

Tanay Tandon 29:43 ... you can-

Ankit Gupta 29:43 It's not actually a legal risk-

Tanay Tandon 29:45 It's not a legal risk

Ankit Gupta 29:45 ... it's just the hospital's own compliance process.

Tanay Tandon 29:46 It's their own internal policies.

Ankit Gupta 29:47 Yeah. And so what does that actually look like in terms of other technological problems you face? Like, what are some, maybe just diving into some technical challenges.

Tanay Tandon 29:54 Yeah.

Ankit Gupta 29:55 Um, I can imagine for something like scribing, at least to me intuitively, that seems relatively straightforward-

Tanay Tandon 30:00 Yeah

Ankit Gupta 30:00 ... as a technical challenge, but perhaps at that scale actually not so much. Whether in that one or in some of the other products you guys have, what are some of the hardest technical problems you guys face in actually making software here? Especially for a company that is selling to healthcare as opposed to-

Tanay Tandon 30:15 Yeah

Ankit Gupta 30:15 ... any other enterprise SaaS company.

Tanay Tandon 30:16 In, in just the case of scribing, simple at first glance, but when you scale, you know, you're dealing with millions of hours of audio that is often being uploaded over shaky networks in the basements of doc- in, you know, a hospital, in a lab, in a pharmacy that's a, you know, freestanding, part of a freestanding clinic in rural America. So you have to build great offline mode and, you know, retention and, and, and the ability to, you know, upload these things silently in the background. And all these, like, traditional te- challenges that consumer apps have solved I think are now being solved in healthcare as well. Number two-You know, we process billions of dollars worth of claims volume every year in our revenue cycle business. And as part of revenue cycle is, I mean, it's Stripe for healthcare, right? You're the interface between the physician and the payer, and the payer's at 100 blocks that make it hard to get paid. Everything from losing the claim to, you know, not telling you that it was denied for a couple weeks so you don't hit your, you know, so you hit your timely filing limit and then can't get paid anymore. We've built models that are constantly checking for all of these threats. Uh, I almost see it as like a, like a cybersecurity problem. Every denial is, is something broke or this is the payer trying to attack the physician. We have to debug what went wrong and help the physician get paid out. A, a good example is all these payers have APIs now.

Ankit Gupta 31:29 Right.

Tanay Tandon 31:29 They just work 80% of the time. What would that means is is that you might get responses that are, y- you know, missing some of the adjudication or there's a, there's a secondary insurance that needs to pay out, and then you need to go separately hit that secondary insurance, or these two insurance companies aren't talking to each other and they both got a medical record but are claiming they didn't-

Ankit Gupta 31:47 Mm

Tanay Tandon 31:47 ... and you have to show them that audit trail. And so the technical challenges are, are very interesting because you're doing this at scale and you need to monitor these processes constantly.

Ankit Gupta 31:55 Yeah.

Tanay Tandon 31:56 Um, but when you solve them, physicians win-

Ankit Gupta 31:59 Right

Tanay Tandon 31:59 ... which is very exciting.

Ankit Gupta 32:00 Yeah. And especially today if they are your advocates, I mean, I think you get this even, I imagine, much faster sales motion-

Tanay Tandon 32:07 Yes

Ankit Gupta 32:07 ... than probably in the early days where if you can show them these technical solutions and they can actually advocate and, like, get your thing incorporated into their hospital, I mean, that's huge for you guys.

Tanay Tandon 32:15 I mean, for our revenue cycle business, the word of mouth is literally my revenue went up by 15%.

Ankit Gupta 32:20 Right.

Tanay Tandon 32:20 And that is the most potent word of mouth in-

Ankit Gupta 32:23 Mm

Tanay Tandon 32:23 ... in the world. And, and that's why we're seeing that business scale so quickly.

Ankit Gupta 32:27 Yeah.

Tanay Tandon 32:27 Um, I think in our ambient business the word of mouth is I save two hours every day, and I did it with this free tool that I found online, and if I wanna get it integrated, it's, you know, like 100 bucks a month or whatever the price is. So that, that's to me why, why, why I think these tools are spreading so quickly

Tanay Tandon 32:43 now.

Ankit Gupta 32:43 And how do you think about yourself in terms of, uh, the types of software you guys have? You know, you call yourself sort of a compound software-

Tanay Tandon 32:49 Yeah

Ankit Gupta 32:49 ... company, sort of a Rippling for healthcare as we've talked about-

Tanay Tandon 32:51 Yeah

Ankit Gupta 32:51 ... in the past. What's the basis for that strategy and how do you guys think about growth and why grow this way versus doubling down on one of these and trying to make that be a massive business in itself?

Tanay Tandon 33:00 I, I think the complexities of healthcare and the way that people get paid in healthcare and really where the operating cash flow lies really make it ... Like, you can only really build $100 billion business in healthcare as a platform company.

Ankit Gupta 33:12 Mm.

Tanay Tandon 33:12 With that being said, you have to start as a point solution.

Ankit Gupta 33:14 Yeah.

Tanay Tandon 33:14 We started as a med device and then eventually turned into this, again, a point solution for a very specific subset of claims, and then over time turned into this platform. Uh, but now that we're this platform, we also have amazing distribution unlocks.

Ankit Gupta 33:27 Right.

Tanay Tandon 33:27 I mean, we get to work with General Catalyst and their health insurance framework. They have 40 health systems that are all signed up. HCA is on our board. It's $100 billion hospital empire. And so I think in the same way that in the 2010s Palantir solved distribution and defense and a lot of call it, like, Fortune 100, uh, use cases and then just aggregated smart people to go work on crazy problems, we're doing that in healthcare. The hardest problem in healthcare, having now spent eight, nine years in it, is distribution. And you can reinvent the distribution wheel over eight, nine years for yourself or you can go build, you know, effectively point solutions as part of this platform-

Ankit Gupta 34:04 Right

Tanay Tandon 34:04 ... um, and not worry about the revenue engine because the backend revenue cycle has that covered.

Ankit Gupta 34:09 Right. As long as you ultimately have revenue cycle management at some part in your platform-

Tanay Tandon 34:13 Exactly

Ankit Gupta 34:13 ... it kind of works.

Tanay Tandon 34:14 Exactly.

Ankit Gupta 34:14 Yeah. I mean, do you think that changes now in this era of kind of doctor-led advocacy of acquiring software? You know, if, if for example it is much easier for hospitals to acquire software than ever before, especially smaller-

Tanay Tandon 34:26 Yeah

Ankit Gupta 34:26 ... clinics, does that change the calculus there at all or do you think, uh, ultimately the same dynamics lie?

Tanay Tandon 34:31 What you will see is a lot of these, like, small couple million ARR businesses-

Ankit Gupta 34:35 Yeah

Tanay Tandon 34:35 ... um, that might be distributed in this somewhat novel way now that physicians realize the productivity gains far outweigh, you know, the getting a wrap on your knuckles from compliance.

Ankit Gupta 34:45 Right. [laughs]

Tanay Tandon 34:46 It, it's an approach. The issue is is that s- the number of companies, and there's like 40 different ambient scribing companies, they all hit like 100, 200K in revenue and then plateau out, and then the next kind of great wall that they hit is, you know, there's probably a dozen of them that got to a couple million in revenue and then they all plateaued out as well. It's not a venture business in my opinion. Like, a single point solution, unless you rapidly expand distribution or you rapidly expand your, your platform, it's not a venture scale business.

Ankit Gupta 35:11 I can imagine then how you think about counter-positioning to what might be many new upstart companies thinking about this. Like, do you think of it as kind of as long as we own revenue cycle management, you know, these folks can basically help us innovate on companies on, on new areas and basically you guys would go acquire them?

Tanay Tandon 35:26 Yeah. Our, our strategy has been, you know, bundle as much as possible-

Ankit Gupta 35:31 Yeah

Tanay Tandon 35:31 ... in terms of we think long term.

Ankit Gupta 35:33 It's kind of the original Microsoft business model too.

Tanay Tandon 35:35 It, it is 100% the original Microsoft business model. And a great example is, um, in the '80s there was a software that came out called Grammatic, and it was, uh, uh, an, a word correcting software or like a gr- grammar checking software, and, you know, it, it ripped. Like, it really took off and, and it looked amazing. I think whatever the equivalent of VCs were in the back, you know, back then, like, were super excited about the business. Like, I'm sure they raised a lot of money from a lot of banks or w- whoever was funding them.

Ankit Gupta 36:00 Yeah.

Tanay Tandon 36:00 And then Microsoft came out with autocorrect-

Ankit Gupta 36:04 Right

Tanay Tandon 36:04 ... as part of Word.

Ankit Gupta 36:05 Yeah.

Tanay Tandon 36:05 And this business just died.

Ankit Gupta 36:06 Boom. Yeah.

Tanay Tandon 36:07 A- and this will happen unfortunately to a lot of these LLM wrapper businesses today.

Ankit Gupta 36:11 Yeah.

Tanay Tandon 36:11 And particularly in healthcare. I think there's a whole host of vanilla point solution scribing companies that have developed, and the minute Epic turns on their own native ambient scribe-

Ankit Gupta 36:20 Yeah

Tanay Tandon 36:20 ... those businesses will go poof because they have no connection to the, you know, revenue cycle, the payment stack or anything more meaningful than just that one layer.

Ankit Gupta 36:28 And actually on, on, on the note of Epic, I mean, how do you think about counter-positioning to them? I mean, they are sort of the kings of distribution in terms of-

Tanay Tandon 36:34 Yes

Ankit Gupta 36:34 ... healthcare, at least for the last decade. Presumably you're trying to take their crown.

Tanay Tandon 36:39 Yeah.

Ankit Gupta 36:39 Um, but how do you think about-Kind of positioning against their, their existing distribution?

Tanay Tandon 36:45 Everything I just said is exactly what Epic would say about us.

Ankit Gupta 36:47 Yeah, exactly. Yeah. [laughs] Exactly.

Tanay Tandon 36:48 And, and so the, the, the way that I think about it is one, one of our core company values is speed.

Ankit Gupta 36:53 Yeah.

Tanay Tandon 36:53 And there are a group of health systems in this country who can't wait for Epic to build these solutions for them over a multi-year product roadmap.

Ankit Gupta 37:02 Yeah.

Tanay Tandon 37:02 Uh, I think the, the best stat that I have here is they're... you know, the two best run health systems in the country and from a, for- you know, from a profitability standpoint are HCA, which is like $12 billion in free cash flow.

Ankit Gupta 37:13 Yeah.

Tanay Tandon 37:13 And then Tenet, which is also billions in free cash flow. Neither of these companies are, are, are on Epic.

Ankit Gupta 37:17 Oh.

Tanay Tandon 37:17 In fact, they avoid Epic like the plague.

Ankit Gupta 37:20 Oh.

Tanay Tandon 37:20 And the reason is, is that Epic often sucks out all of the operating cash flow of the academics and businesses-

Ankit Gupta 37:25 Right

Tanay Tandon 37:26 ... that they work with. We have these like multi-hundred million dollar implementations. And-

Ankit Gupta 37:29 Yeah

Tanay Tandon 37:29 ... the, the, the way that I see it is if you wanna be a fast moving growing business, you probably can't be on Epic because the CIO's office becomes this captured asset, and they're just waiting for Epic to release stuff. Or at least Epic can't be central to your strategy. Maybe you use them for your EMR, but you're, you're building the system of engagement and other tools on top of it and around it. Um, and, and we aim to be that platform for that system of engagement on top of EMR.

Ankit Gupta 37:53 And it seems like you're innovating on a very different go to market compared to them too. To your point, they're probably going to the CIO's office.

Tanay Tandon 37:58 That's right.

Ankit Gupta 37:59 You guys, it sounds like, are experimenting with ways to go straight to doctors and then kind of make your way to the CIO's office from doctor demand as opposed to from some large enterprise deal that's forced on everyone.

Tanay Tandon 38:08 Yep. And ultimately, you have to earn the trust of the CIO. There's no doubt about that.

Ankit Gupta 38:11 Yeah.

Tanay Tandon 38:12 But you can build a lot of momentum-

Ankit Gupta 38:13 Yeah

Tanay Tandon 38:13 ... and add a lot of value, uh, through this physician-led adoption. You know, even at our largest health system partners, we have forward deployed engineering teams that will sit and, you know, just work with the medical directors and the leading physicians in that facility to try to make their day a little easier, and that's it. That's all their job is. Um-

Ankit Gupta 38:32 I mean, much like you and your co-founder in the early days. [laughs]

Tanay Tandon 38:34 Ex- exactly.

Ankit Gupta 38:34 Yeah.

Tanay Tandon 38:34 We, we try to replicate what worked, uh, in the, in the early days-

Ankit Gupta 38:38 Yeah

Tanay Tandon 38:38 ... into these forward deployed pods, and so far it's yielded. Like we... a lot of our net new products and a lot of our net new initiatives have come from that.

Ankit Gupta 38:45 Maybe changing gears a little bit at, at the end here is I'd love to just talk a little bit about how you see the future of healthcare broadly. I mean, you obviously-

Tanay Tandon 38:53 Yeah

Ankit Gupta 38:53 ... have had a front row seat to both participating in and shaping what this field has looked like for the last several years now. On the, on the flip side, from, from my perspective as a patient, um, it feels like not a lot has changed-

Tanay Tandon 39:05 Sure

Ankit Gupta 39:05 ... from my experience as a patient over the last, let's say, 20 years. Again, if I were to go to a doctor in 2005 versus 2015-

Tanay Tandon 39:10 Yeah

Ankit Gupta 39:10 ... versus today, sure, more stuff is on a computer, but kind of fundamentally, I'm kind of waiting for the same amount of time and-

Tanay Tandon 39:15 Yeah

Ankit Gupta 39:16 ... talking to more or less the same people, and maybe there's a couple new things, but for the most part it feels very similar. One, do you think that's an accurate characterization? And then also, how do you think of the next 10 years? Like, do you think it's gonna look kind of similar for patients this upcoming decade?

Tanay Tandon 39:28 I, I think for the most part I, I agree, which is that the core of the experience hasn't changed. I think we're starting to see innovation now on the fringes in that there's a lot of things that you had to go in for that you can now do via telehealth visit.

Ankit Gupta 39:41 COVID sort of accelerated a lot of this.

Tanay Tandon 39:42 Definitely accelerated a lot of that.

Ankit Gupta 39:44 Yeah.

Tanay Tandon 39:44 And, and that's great. I think a system that is inherently supply constraint, the more that you can take out of, you know, having to actually show up at this facility and, and, and, you know, wait for someone to see you, the better it is both for the system as well as for the patient. Where I think we're starting to see now a rapid adoption is the physician's life is starting to actually become easier in that these LLMs are saving them time provably-

Ankit Gupta 40:08 Yeah

Tanay Tandon 40:08 ... every, you know, couple hours every day. And because of that, they're either gonna... you know, their panels will open up. They'll be able to see more patients.

Ankit Gupta 40:14 Yeah.

Tanay Tandon 40:14 So getting an appointment with a specialist hopefully starts feeling a little easier, uh, you know, mo- moving forward. But then number two, I think on the whole, these systems are starting to adopt AI-based solutions for things like their front desk to assist with, you know, call automation, um, the, you know, patient engagement. We have a system that for colonoscopy prep, it's called Commure Engage. It will send you a reminder and converse with you based on the source material and recommendation from the physician, and it boosts and improves no-show rates by 50%.

Ankit Gupta 40:43 Hmm.

Tanay Tandon 40:43 Um, because the, the prep work is done and, you know, you don't end up having to cancel the appointment last minute-

Ankit Gupta 40:48 Yeah

Tanay Tandon 40:48 ... because you mess something up. And, and so those metrics are all moving in the right direction. I think where what healthcare should become with LLMs in the next couple years is, you know, you should get your most critical care in a hospital or in a, you know, in front of a physician where there really is something like, like, you know, phys- physiotherapy, like a p- like a PT actually taking care of you.

Ankit Gupta 41:09 Right.

Tanay Tandon 41:09 Um, or-

Ankit Gupta 41:09 Surgeon operating on you.

Tanay Tandon 41:10 A surgeon or a deep complex diagnosis that requires multiple tests in one day. Those things should happen in, in, in an office. But with LLMs, more and more care I think can transition out of the home with sensors that monitor the patient, virtual care, um, and, and I think that world is finally becoming real.

Ankit Gupta 41:26 And I... what do you see the transition in that world looking like? I mean, there's all these pretty deeply baked incentive systems that incentivize bringing people into the hospital even for relatively small things 'cause you have to bill for it.

Tanay Tandon 41:36 Yep.

Ankit Gupta 41:36 And to your point, a lot of the revenue ultimately comes from RCM. Do you see that, those, those sort of entrenched financial motives actually preventing that future from happening, or do you see that it's gonna happen inevitably just from like kind of this abundant intelligence age we're, we're entering?

Tanay Tandon 41:51 I think it will happen inevitably from the, you know, this, the, the a- abundance of intelligence that's emerging. I think a lot of your, your fringe care will, will again just be things that patients can do entirely on their own. And as a result, health systems will be forced to really specialize in, in doing those high margin, high dollar procedures that they're uniquely good at.

Ankit Gupta 42:11 Yeah.

Tanay Tandon 42:11 And because of, uh, that specialization, I think the quality of that care will improve as well. And, you know, you see things like intuitive surgical and like robotic care actually. The fact that it's a thing in, in, in, in the States is-

Ankit Gupta 42:22 Yeah

Tanay Tandon 42:22 ... is, is pretty remarkable. So I think at the, at the highest ends of our spectrum, technology has in fact improved quality of care meaningfully.

Ankit Gupta 42:28 Yeah.

Tanay Tandon 42:28 There's like new immunotherapies cleared every year-

Ankit Gupta 42:29 Right

Tanay Tandon 42:29 ... et cetera. And then at the very lowest end of acuity in terms of basic telehealth, that's improved as well.

Ankit Gupta 42:35 Right.

Tanay Tandon 42:35 And it's this kind of middle that's now getting squeezed-

Ankit Gupta 42:37 This massive middle. Yeah

Tanay Tandon 42:38 ... by both, by both sides. And hopefully that the, the rate at which, you know, that, that middle gets compressed will be fast.

Ankit Gupta 42:44 I mean, one of the areas you see the kind of big research labs most excited about is, you know, like Microsoft, for example, put out this, uh, thing called medical super intelligence.

Tanay Tandon 42:52 Yeah.

Ankit Gupta 42:52 Uh, on the path to medical super intelligence recently. And there's this sort of e- excitement around the possibility of actuallyUm, in many ways, kind of replacing or, or at least very heavily augmenting, but ultimately, fundamentally in the long term, replacing the kind of-

Tanay Tandon 43:05 Yeah

Ankit Gupta 43:05 ... fundamental kind of diagnostic process that a lot of doctors do with super intelligent AI systems. You know, ones that could order tests and then respond to feedback and iter-iterally work on those. I mean, how do you think about those? Like, do you, do you see that being as part of the future? And also, if that were, you know, what do we need to do now to make that future happen? Like, what's kind of missing in the current world to make that happen?

Tanay Tandon 43:25 When it comes to ordering or when it comes to as- assessing a test and then recommending a plan of care, these models will probably surpass humans. And if they have, if, if not, like, already have, have surpassed humans. The, the idea is that just the way that our regulatory system is set up from a malpractice standpoint, a litigation standpoint, a billing standpoint, you probably still want a responsible party. But I think these health systems will be, be mega adopters of a lot of these tools of intelligence because it will probably help them from a malpractice standpoint.

Ankit Gupta 43:54 Right.

Tanay Tandon 43:54 If you can point to a model has synthesized millions of data points and come to this conclusion-

Ankit Gupta 44:00 Right

Tanay Tandon 44:00 ... and we're, you know, basically going through th- it- its recommendations, that's a way better world than doctor kind of stuck his finger in the air and guessed what was happening.

Ankit Gupta 44:08 That's what it is, yeah.

Tanay Tandon 44:08 And so I, I see physicians embracing what we call these super intelligent co-pilots that synthesize information and, and take action. You will probably still for complex things need to see the physician, get that final assessment, and then the speed and accuracy at which you go from not knowing what you have to then something happening, I think that will get compressed, which is net good. The reimbursement modalities, I'm, I'm not the world's biggest believer in this, like, value-based care world. And, you know, we've been talking about it for like 15 years. I, I just think there's something about simple capitalism that works well in America, which is here's a service, here's a cost, and, you know, we will improve the accuracy with which we render XYZ services. And maybe that, you know, that requires better auditing or that requires these super intelligent systems not recommending unnecessary or incorrect medical procedures.

Ankit Gupta 44:58 Yeah.

Tanay Tandon 44:58 Um, but this, this procedure driven healthcare world seems to work. Like, America does have good healthcare outcomes-

Ankit Gupta 45:03 Yeah

Tanay Tandon 45:03 ... relative to the rest of the world.

Ankit Gupta 45:05 Yeah, and per- and perhaps, you know, if there's significantly less unnecessary care happening where people are able to triage themselves-

Tanay Tandon 45:11 Yes

Ankit Gupta 45:11 ... in, in conversation with some sort of super intelligent-

Tanay Tandon 45:14 Yep

Ankit Gupta 45:14 ... chat system or whatever that system might be in the future with video and with sensors and whatnot. Perhaps that opens up the opportunity for medical professionals to focus on the cases where you can actually deliver really great outcomes versus-

Tanay Tandon 45:26 Yep

Ankit Gupta 45:27 ... clogging up ERs with people who don't need to be there.

Tanay Tandon 45:28 Well, 100%.

Ankit Gupta 45:30 What kind of future do you think that that actually looks like 10 years from now then? Like, did you see yourself... Do you think we're gonna go to the doctor every year? Do you think we're gonna, um, only go when, like, we actually have a catastrophic issue only

Ankit Gupta 45:41 or something in between?

Tanay Tandon 45:42 I, I think in 10 years you're gonna have a lot... You're gonna have sensors kind of built into the home. You're gonna have sensors that are, you know, wearables on patients. The Apple Watch and AirPods are becoming medical s- medical devices very quickly.

Ankit Gupta 45:53 Yeah.

Tanay Tandon 45:53 And that's a, that's a good thing because that passive care where, you know, we can detect things like AFib and-

Ankit Gupta 45:59 Yeah

Tanay Tandon 45:59 ... you know, detect spikes in certain biomarkers is really good because that's how you treat them very, very early. The concept of health insurance and the concept of how care is rendered is gonna look a lot more like how our cars are, are handled-

Ankit Gupta 46:10 Oh, interesting. Yeah

Tanay Tandon 46:10 ... in a sense like auto insurance where-

Ankit Gupta 46:12 Yeah, it's like catastrophic insurance in a way.

Tanay Tandon 46:13 Catastrophic.

Ankit Gupta 46:13 Yeah.

Tanay Tandon 46:13 And, and so when something bad, you break your arm, you have cancer, or you have a, you know, very complex disease, there will be an insurance mechanism and really your insurance will be focused on that kind of care. And then I think the rest of the care, it's actually cheaper for it to be out of pocket and for it to be, you know, outside of the loop and complexity of the insurance system, where you can just get a direct prescription or you can, you know, see a provider on telehealth or even in person for basic therapy. Um, and b- because the system will have shrunk and we have deleted parts, it will become a more efficient system.

Ankit Gupta 46:42 And do you also see it reverting kind of back to that version? You said in the '80s and '90s it was great to be a doctor.

Tanay Tandon 46:47 I think so.

Ankit Gupta 46:47 Do, do you see in many ways the sort of consolidation we see happening in this field will at least slow down and perhaps even revert back to seeing more people open private practices?

Tanay Tandon 46:54 I, I really think so. I, I, I would love a world where the market cap of a UnitedHealth is, you know, a fifth-

Ankit Gupta 47:01 Yeah

Tanay Tandon 47:01 ... but every doctor is a millionaire.

Ankit Gupta 47:03 Right.

Tanay Tandon 47:03 Like, that is a good world for America because patients are getting treated better. The people that are actually rendering care-

Ankit Gupta 47:09 Right

Tanay Tandon 47:09 ... are where value is accruing. It is insane to me that if you think about it, the most valuable healthcare company in the country, what they effectively do is, like, send you a plastic card in the mail once a year.

Ankit Gupta 47:18 Right. [laughs]

Tanay Tandon 47:18 Yes, there's, you know-

Ankit Gupta 47:19 Right. Sure. Yeah, totally

Tanay Tandon 47:19 ... there's straw man, there's more that they do.

Ankit Gupta 47:21 Yeah.

Tanay Tandon 47:21 But really at its core, that is your interaction with them. [laughs]

Ankit Gupta 47:23 Yeah, totally.

Tanay Tandon 47:24 And, and, and-

Ankit Gupta 47:24 Then being denied claims perhaps

Tanay Tandon 47:26 ... and then denying claims.

Ankit Gupta 47:26 Yeah.

Tanay Tandon 47:27 And, and so it is, it's an insane system. It needs to change. Way too much value is accrued at that layer, and I think it needs to come back to the physician.

Ankit Gupta 47:34 Then maybe just to, to wrap things up, you know, now you've, you've been at this for, for quite a while. There's many new founders excited about thinking about this current technological moment in healthcare and AI.

Tanay Tandon 47:42 Yeah.

Ankit Gupta 47:43 You know, what advice would you give them in terms of how to compete with someone like you guys, um, but also how to build a business that can endure and kind of capture this current technological moment?

Tanay Tandon 47:52 Uh, I think our biggest learning is get in front of the customer and then just solve problems for them, and, and start with one specific problem, even if the, regardless of how small it looks. Our fir- You know, our initial TAM was laughable.

Ankit Gupta 48:04 Right.

Tanay Tandon 48:04 It was 100,000 patients in the entire country.

Ankit Gupta 48:06 Right.

Tanay Tandon 48:07 But people and, you know, our investors and our team and our, you know, early, you know, founding engineers, they took a bet on us because they believed that we could take the momentum from that to build something even bigger. Uh, and, and so I would just say don't be afraid of starting very small and very specific because that is more valuable in the long term than, you know, trying to build a platform from out, right out the gates. The other thing that I will say is some of the best companies being founded right now are folks that came from the Palant- you know, did a tour of duty-

Ankit Gupta 48:35 Yeah

Tanay Tandon 48:35 ... six, seven years at a Palantir. Solved, didn't have to worry so much about distribution and just solved problems for customers and then saw that scale and learned about the distribution. Um, and so, you know, my selfish pitch is like if you're building in healthcare, one of the fastest ways to both become very wealthy is compound at a company like Commure.

Ankit Gupta 48:53 Yeah.

Tanay Tandon 48:53 And, and then also learn these skills that you would otherwise have to kind of learn de novo that, you know, might take years i- i- i- in, in order to amass.

Ankit Gupta 49:00 Yeah, I totally agree. I mean, I think one of the best ways to think about it, being, becoming a great startup founder is to work at another great startup, one that's growing and-

Tanay Tandon 49:07 Yep

Ankit Gupta 49:07 ... one where you can get exposure to customers. I think that kind of forward deployed role you describe feels a lot like the experience-

Tanay Tandon 49:12 Yes

Ankit Gupta 49:12 ... of an early founder, maybe with perhaps less total independence, but a lot of the same skill set that you might gain.

Tanay Tandon 49:17 One- 100%, yeah.

Ankit Gupta 49:18 And ultimately focusing on making things people want. Makes sense.

Tanay Tandon 49:20 Yep. Make things people want.

Ankit Gupta 49:22 Awesome. Thanks so much. Thanks for joining us.

Tanay Tandon 49:23 Thank you.

Ankit Gupta 49:23 This was great.

Tanay Tandon 49:23 Appreciate it. [outro music]