Hello Patient raises Series A — building specialized voice AI for healthcare that generic platforms can't replicate

rest of your day. Great to catch up. Thanks a lot, Batman. See you. That was fun. Code country. Another Cohen coming into the studio, breaking down big fundra exciting. I'm excited for this one. Uh legendary poster. One of the greatest to ever do it. very excited to have him on the show. Andrew in the chat.

What about what's happening? We need to give Andrew more context. We put these on not for you, although you are from Texas, but for the uh Warp, the CEO of Warp, but we'll leave them on because they're fun. I thought you guys put them on for me. I was going to ask that. That was my first question.

Uh no, no, but but uh but but yeah. Do you ever wear a cowboy hat around the office? I do not. I have boots, not a hat. Okay, there you go. Boots. Boots are Boots are strong. Uh, what's happening? It's great to great to finally have you on the show. Thank you guys for having me.

I needed something newsworthy enough to make it on here. So, I had to raise a round just to get on the show. Well, I think you've been on many times via your post. Via your post. We have reacted to many of your posts. So, long time long time guests. Uh, but what Yeah.

give it give us the whole kind of back I mean since it's your first time on the show uh in person give it give us kind of quick history of the company and the news uh quick history is we got started last April after a team of us had been at Carbon Health for three and a half years um left in January started the company in April raised around got to work and then fast forward 16 months later we just closed our series A and it's been a fun time so congratulations Wow.

Look at that. I thought you walked I thought you walked away. You're like, "Fuck this. I'm out. " No, we got a gong. No, we got it going. Congratulations. Um, how are you positioning the movie right now? Yeah. Yeah.

The main thing that I'm trying to understand from like like your your journey like makes total sense like being deep in the weeds and and understanding what what um you know from your time at Carbon it feels like this category like so many I'm sure you're you're getting sick of like refreshing like Techrunch and seeing another like voice uh AI company that that that uh is going after the market broadly but like how is the what's the shape of the market?

How is it evolving? like where are you guys what is what does your GTM look like and all that good stuff.

Yeah, I mean here's my general take on the space is like you've got a group of us who are specifically focused on healthcare AI or like you know whatever voice SMS conversational AI for healthcare you kind of have to be specialized on it uh in order to make it work and I think that's why you know we saw Sierra just raise at 10 billion you've got all the call center companies with their own flavor of like we're no longer shitty IVRs we like have a conversational AI now and so problem is that as you like start to hear about how their implementations are going you start to hear how they from like across different verticals.

They're just not doing that good of a job at it because they don't understand sort of the nuanced crazy stuff that happens in these healthcare clinics.

And so we we literally have to like almost go on site with customers and understand their workflows, their appointment triaging reasons, like how you actually get a patient to the right place and then read and write back into their systems of record, which many of them, you know, unlike, again, I'll use Sierra as the example, but like unlike Sierra being able to just integrate with Shopify who has great APIs to go do like, hey, what's my tracking number?

What's your return policy? Can you check the status of my order? We have way harder to work with systems of record. And I think a lot of folks just don't want to go put in the work or understand how to go make those things happen.

And so I think you'll see companies like us be a lot more successful in getting these practices live. Um I think you'll see some of the larger companies maybe win some deals and then go spend 9 months building custom software to go make it work.

And then I think you'll see most people pivot out of healthcare over the next couple years because just because it's conversational and generative and open AI exists doesn't make the work any easier to do right now. And that's kind of like the return to the way the industry has always been.

I feel like whenever you dig into healthcare, it's like, oh, well, they're not using they're not using the standard SAS product for, you know, it's the it's like the the whole genre of vertical SAS like is the textbook example where maybe they're using different ERP, different payroll, different help desk software, help, different CRM, like they're they've always had their own little area carved out.

Uh, and I don't know how much of that is just like compliance, but it's like it's certainly a unique thing. What's the gold standard now? Like what what are you guys trying to deliver on the product side?

Because I I saw a screenshot you shared of Sierra on their uh you were you were throwing a little shade on the day of their on the day of their launch. It was an exchange where you're just like can you find me some green shorts? And they were like, "Well, we have lots of clothes. Like why don't you look around? " Yeah.

It was pretty funny. Um but like what what are you guys trying to deliver? And what do you what do you think bestin-class is right now? And do the models even need to get better for you to deliver on your vision or or are they are they good enough that it's just more about like deep integration and and workflows?

Yeah, I think that there's a lot of tension in someone like a Sierra who's got a very almost deterministic style chatbot and that's been around forever. I mean, what they're doing is not new. they're just saying, "Hey, it uses generative AI versus what you used to do, which is keyword matching.

" And then sharing some response that you had queued up that was approved by the customer in the chat experience. Um, and then on the whole other side, you have an experience like chat GBT or Claude, which is purely generative, very, very general purpose.

Anyone can chat with it and you can really get it to do whatever you want it to do within, you know, as long as their guard rails don't pick it up. And somewhere in the middle is a conversational experience where you call in and you say, "Hey, I'm having this this issue.

I have this I need an appointment like here's my symptoms and the agent has a defined scope of work but it still needs to follow somewhat of a deterministic path to get you to the outcome right so in order to schedule I have to look up your account verify who you are find the location that you're looking for find available slots find available providers and then ultimately book the appointment and write that back to the practice management system so there is a workflow or step that has like steps that have to happen in some sort of order to do that right end to end is very complex A year ago, even when we got started, you really couldn't do scheduling end to end unless you were building what was a phone tree of like, you're in this step right now.

Choose one of these three options. Now you're in this step, choose. And that's not what I think anyone wants to be the gold standard for an experience when you call into your provider. And we've always been fully conversational from day one.

And I think over the summer, we made a bunch of breakthroughs on like how we build a whole suite of agents that work together to get the job done.

And so, for example, if you're calling into one of our practices now and you say, "Hey, I'm making an appointment for I'll use like Med Spa as an example for Botox, there is a Botox agent that all it knows how to do is schedule Botox, but it's still conversational.

" And then if you're like, "Hey, I actually need to switch to a laser hair removal appointment. " Um, then it switches to the laser hair agent. The patient never sees anything, but in the background, we're doing a bunch of multi-agent switching and that's the only way to make these things work and still be generative.

And they still have failure rates like 5 to 10% of cases. is it doesn't work as expected. You can imagine all the dumb [ __ ] that patients say. It's like completely random.

And so, and you can't plan for all of those scenarios, but you just have to get This is why I don't think AI doctors will be a thing anytime soon because that margin of error will always exist and it's like they don't want to take liability or responsibility for that.

We can get away with a little bit more margin of error because we're doing administrative functions.

But that's the experience we want it to be is you call in, you know that it's AI, but you're having a conversation with it just like if you were talking to Chad GPT's voice model and it can do the job end to end even if it's scoped to a limited set of jobs. Yeah.

How much of uh how you build this is like uh develop an RL environment to actually post-train a model to interact with all the back office and administrative systems versus kind of like create your own deterministic SAS layer that then your agents are kind of interacting with or or are just kind of like function calls within deterministic like business logic.

It's very much the latter. It's like we've got this app layer where it understands an ontology of a practice. Services, locations, providers, all of those have their own specific context, right? There is um different protocol if you're scheduling one appointment versus the other.

Maybe you're like three steps into a triaging workflow now. And then they do have tool calls where they get to say like I need to create an appointment. I need to find available slots. I need to create the patient account.

All of those tool calls have their own business logic and agents that they interact with on their own that it's all very constrained. So you kind of have like 70% as prompt engineering, 30% as code in the background to be like, "Hey, that's not the phone number the patient's calling in from.

You can't look up that patient, right? " Because there's security uh factors to consider. So definitely a lot more of the latter than it is like any sort of RL environment where we're like you don't really the conversations don't change that much.

So we rely on the foundational models to handle a lot of the edge scenarios where someone's trying to go off rail and say something that's not in scope of the agent. That makes a ton of sense. Thank you. Do you last last question?

Um the like do you guys internally view yourselves as building vertical software with the end user experiencing the product as an agent?

because I feel like uh there's been a lot of companies come out over the last year that saying like we're building AI agents for XYZ and then if you actually drill down into like okay what are you doing and like what is the experience of a of a of one of your customers it's like SAS right and that's like it can be AI enabled to be clear we're extremely bullish about that yeah we're and and we're s and yeah I'm super bullish about it but I but the way that you're describing this and the companies that that are that I think are are are sort of doing good work broadly or like it's not like you're trying to sell that you're just completely reinventing like an entire business model.

It's more like we're building really valuable software and automated workflows for companies and the end result is that the p is the patient or the user will have a a great experience. You sell the solution not the technology. Yeah.

And I feel like you're one of the first companies not you know who knows but maybe one of the first companies kind of embrace the new stance. You don't have aai domain for example. No. Uh I I don't think the practices really give a [ __ ] that it's AI versus some other system. Yeah.

They uh they care like we ult I've said this I said a few things from day one but like one is that there is inherent product market fit in what we're doing as long as we can make the agents work as expected.

And so if I can schedule appointments reliably, if I can refill prescriptions, if I can do all those things and the front desk doesn't have to do it or the call center doesn't have to do it, like everyone will buy that if it's cheaper, faster, better, you know, whatever you name it.

Um the second is that yeah, they just like don't care that it's AI. They think it's interesting. What's nice is like every group has an AI strategy. They don't know what that means yet and so but they know they want to like partner with a company to go do that.

And so we treat it is all partnerships right now because it's so early, but we're definitely building vertical services. I would say like that use software to make it really efficient and you don't have to go hire people now to go do the work in most cases.

Um but yeah, it doesn't matter that if it were if it were I suppose an IVR that got like a phone tree that was able to do the same thing like someone would buy that too. they would just get replaced by the thing that's better and has higher conversion, better patient experience longer term.

And so, yeah, that's really the philosophy. And then longer term, we are going deeper into the stack in terms of the software that we will offer to the clinics to also help them do their jobs better when it's not the AI doing the job.

And so we look at it as like right now we're doing very specific bespoke services for the group like answering calls and scheduling or doing outbound campaigns and texting a bunch of patients saying hey you're overdue for your annual wellness visit or your vaccines or whatever it is and then having a conversation and again getting them scheduled.

Longer term uh you can imagine like we build more of the software that sits again on top of their practice management system but that helps the actual clinic teams do their jobs more efficiently as well. It's just deeply integrated with the AI component. Fantastic. Thank you so much for taking the time.

Great to have you on. Join anytime. Great questions. We'd love to have you.