Interviewer / Host (5:26)

Oliver Cross, you are the co founder and CEO of Zopdoc. Welcome to Decoder.

Oliver Karas (5:31)

Good to be here. Thanks.

Interviewer / Host (5:32)

I am very excited to talk to you. There's a lot going on in how apps are built, how people experience services on devices. In healthcare in America, AI is tied up in a lot of that. I think there's a lot of that to unpack with you that I'm excited to get into. But let's start at the beginning. I think people understand one version of what ZocDoc is. You need a doctor. You open this app, maybe you'll find one. But it's a lot more than that. Now explain what you think Sockdoc is.

Oliver Karas (5:59)

Zocdoc is really a platform that connects patients and doctors wherever they are. Obviously, as you point out, the marketplace, the app, is really well known where people can just do that self directed. But we are making sure that wherever you are as a patient, you can get access to care. We have a partnership with some health insurance companies, Blue Shield of California, for example, when you go to their website, you can get access to care. We help veterans get into care. We have other surfaces that are very annoying, like the phone, which seems weird for us to do given that we started out to eliminate the phone from the healthcare process. But we've recently released a product that allows you to call into your doctor and schedule an appointment with an AI agent completely autonomously. So our current trajectory is really how do we make getting access to care easy for any patient anywhere?

Interviewer / Host (6:54)

So zocdoc was founded, I would say, in the era of smartphone apps. We're going to move everything into a screen on a phone and we're going to have marketplaces, especially these two sided marketplaces. Uber for doctors. There is a way of talking about apps and services at that time, which I think was very powerful, led to a lot of investment, led to a lot of great companies. That's changing now. Do you still think of yourself in that model or do you think ZocDoc is going to have to be something else in the future?

Oliver Karas (7:23)

I think we're definitely an app model and we have figured out how to do access to care better than anyone else in the US when you pick up the phone and you start dialing for doctors, it takes you on average 30 days till you can actually see one. On Zocdoc, the plurality of all appointments happen within 24 hours. Nearly all of them happen within 72 hours. That's an experience that's an order of magnitude better than what you get through the phone and the old modalities. But we're not trying to take sort of the platform captive. We are opening it up for others as well, some of the health insurance players that I mentioned before. But we are in generally thinking of ourselves as something that can be useful in meeting patients where they are and allowing them to see their doctor.

Interviewer / Host (8:09)

So that expansion into telehealth, right, it's not, I'm just going to book a doctor appointment and go to an office. So I'm going to book a doctor appointment. The doctor will show up here. There's a lot of competition in that space. Zoom just sort of accidentally started a telehealth business in the pandemic because they existed, you know, other providers, insurance companies, want to be in that business. Is that a future growth area for you or is that just a continuation of the services you have now?

Oliver Karas (8:37)

So we offer telehealth, but if you're totally honest, and this was visible, you know, early on, patients just don't really want it, right? So we offer telehealth options. We offer in person options in everything but mental health. 95% of all appointments are in person. And here's the interesting thing. Even doctors that offer both telehealth and in person visits, they get more bookings than doctors that only offer one or the other. But the bookings are all for the in person visits. So the patient really only values the option of, okay, maybe in the future I want to see that doctor in a telehealth visit. But right now I have a body, right? Like, they want to look at my mouth, they want to listen to my heart, they want to poke my abdomen. And one of the things about Somatic medicine is that telehealth is a little bit like telepizza. It's great, except you can only eat the pizza when you're in the same room with it. Right now, mental health is very different. In mental health, the picture is exactly reverse. Nearly all of it is happening remotely. And it just has tremendous advantages for both parties to do that. So I think it's a very nuanced picture. And one blanket statement isn't going to do it complete justice. We offer that as we offer all other modalities. We offer urgent care and primary care and 250 specialties all the way to cardiac surgeons and an oncologist. So you can find really any type of care on zocdoc.

Interviewer / Host (10:10)

One of the. I think one of the interesting things about Zoom, for example, or other telehealth services is the notion that you will end up speaking to an AI. So I interviewed the CEO of Zoom, one of the strangest episodes of Decoder in history, and he said, the future of Zoom is that I will make an avatar of you and then your robot avatar will go to your Zoom meetings for you and you will go to the beach. And I thought I said to him, at the end of this, all the avatars will be having meetings and I don't know what we'll be doing. He said, that's interesting. That might be fine for a number of corporations. That's very different for a doctor or health care organization. Right. Where you've outsourced the decision making process or the patient relationship to an AI or an agent or an avatar, it feels dicey. It also feels like something consumers will increasingly demand. How do you think about that in your platform?

Oliver Karas (11:00)

Yeah, so I have some skepticism about that future, mostly because I do think there will be more self medication. Right. Dr. Google is going to be replaced by Dr. AI and the patient will develop their own judgment where they think that an AI is good enough to give them guidance and where they actually want human judgment. And I think it would be maybe misleading to blur the line and say, oh, you're talking to AI, but I make it look like you're speaking to a human because the patient self selected into I want humans eyes on that because I think the potential for an error is too great and the change in outcome is too significant. So this is where I think we just need to be honest to ourselves. Not everything that is possible is actually useful.

Interviewer / Host (11:48)

So you have an AI part of the platform now called Zoho. It's an assistant, as you said. It helps with scheduling, it helps with, I think, customer service that's expressed. You described it as on the phone you can call and talk to a voice, it will talk back to you. Do you feel the same tensions there that people have self selected into an AI or are they just calling the phone and getting a.

Oliver Karas (12:09)

So yeah, obviously they know it's an AI and they can opt out of that experience frequently. Playing scheduling Tetris on the phone with another human isn't actually that fun, particularly when you have to wait 20 minutes to actually talk to that person. And people are okay with that. But one of the big misunderstandings on how AI solutions work is that just automating the work of the receptionist or the call center agent. I think if you aim for that, you're aiming too short as an AI enablement company. Because what you need to think about is, hey, now that I have this AI and I have essentially unlimited bandwidth, how would I design this job from scratch? And so, for example, for us, it's not okay, how does our AI compare to human agents, but it's actually measuring the effectiveness of all the human agents, knowing the effectiveness of the AI for every type of patients, and then connecting the patient to the right resource. So if you call in for a routine thing, you just want to confirm the office location or you want to reschedule an appointment you've already made. Well, do that with an AI because it's so straightforward. You'll get past the service, it will be super friendly. But if you have a complex question, well, let's connect you to the human that is best informed about that in the practice. And the AI can know that, and it can dynamically triage these patients to come in and give you a much better experience than you had before. So you should really rethink your call center. Not as, how do I reduce my expenses in a cost center, but how do I actually turn this into a profit center where I now lose fewer patients and have less leakage on the front end and make sure that patients have a great experience when they call me.

Interviewer / Host (13:49)

So let me push you on this a little bit. So the idea that I need to reschedule an appointment, I feel like that has been conclusively solved by smartphones. I don't necessarily need to talk to a robot. I actually want to use the visual interface of my smartphone and hit the button. And maybe I'm actually taking the action, and maybe I'm just sending a note to another back whatever it is, but it feels like I'm actually doing it, and that problem feels solved. I have some complex medical question, and I need to dive through a series of screening questions to find the right provider and schedule that. That does feel like a natural language process. Tasks that AI might be good for, but then that's also a little bit diagnostic, right? It's a little bit. You need some insight there. How much insight are you willing to let your AI have in that process?

Oliver Karas (14:35)

So it's actually very interesting because what you say makes Absolute sense, minus the fact that as a patient your experience is actually you have hundreds of different logins to all these different Dr. System. Obviously I hope everyone uses Octoc that you have only one login, but in reality some patients still use the phone to make the appointment and they don't think about the app as an alternative. So you'd be surprised what percentage of calls that come in are actually simple things like scheduling. They clog up the pipes for the patients that are coming in and calling about complex issues. So there is just probably a transitory period until everyone uses Octoc where these reschedules still happen over the phone. But then in terms of the insight, so what we see is actually that humans don't perform equally on all complex issues either. And so we can measure what sort of the successful conversion rate for a call that comes in to the average human, to Zoho, to other AI solutions to the best humans. And when you look at this, and there's been an independent study that has been done on that recently, but they found, okay, zocdoc, among the AI solutions is actually the best. They have a conversion rate of roughly 52% where everyone else was below 40. And humans are typically like the average human is in the high 40s. So comparable to the AI, the best humans are at 65. Right. So they are dramatically better. But are there 65 for everything and should you use them for everything? No, you should make sure that whatever they are doing, you teach to all the other people that are answering your phone. So you up level in general, but then also you want to make sure that you route the patient that actually has this problem, that this call center rep is expert in that patient and that expert need to talk to each other, not some other random person on either end of that.

Interviewer / Host (16:36)

So to ask that question a slightly different way, that feels like it requires some expertise, some insight into what the patient is saying, into what services are available. And there's got to be a limit, right, to how much thinking you want the AI to do, how much judgment you want the AI to do. That feels like the problem writ large for our industry. Where are we going to stop the AI and say it's time to talk to a person?

Oliver Karas (16:57)

Well, so the AI needs to be sort of self conscious in that way. Right? And that's why you can't just leave it to the AI. I think if you, anyone who uses LLMs finds that they are too confident when they shouldn't and they're not curious enough when more questions would actually be adequate to get to the correct solution. And so we have solved this in a completely different way where we have sort of the deterministic orchestration layer that then uses LLMs selectively to make sure we parse the answers of the. Of the patient correctly. But we have a master plan, and we know when a conversation goes outside the bounds of the master plan and should be transferred over to a human. And therefore, you know, like, we, we can sort of take accountability for that. You know, like, this is very different from just dumping everything in the context window of an LLM and praying for the best.

Interviewer / Host (17:47)

Okay, I want to hold on that and come back to it because I think the entire industry is restructuring itself around that problem. And that's one very important solution. But I do want to ask the decoder questions kind of understand Zocdoc as a company. How is ZocDoc structured right now? How many employees do you have and how are they organized?

Oliver Karas (18:04)

Yeah, so if you're a little bit over a thousand employees, and we are still functionally structured, so we have a head of sales, a head of marketing, ahead of government relations and what have you. And the reason why that works for a company our size and why I think it's going to work is because of our quite unique history. We didn't have a straight lineup. Right. Like we've been around for a long time. We went through a major, you know, business model transition, turnaround you could call it. And it had created a kind of cohesion, that sort of A1ZocDoc philosophy still works. Right. Like everyone in leadership is gold against the same number. And it's a number for zocdoc and its totality. And this is why we can bring functional teams together. And we don't get the typical corporate politics that make this not work.

Interviewer / Host (18:51)

So what's the number? When you say there's one number to go against, what's the number?

Oliver Karas (18:56)

So it's a revenue number, it's a profitability number, and we sort of fuse that together into one score.

Interviewer / Host (19:03)

The business model change you're talking about was you went from flat fees for doctors to per patient referrals. You've given a lot of interviews about how that unlocked growth, and now you're profitable. The doctors didn't love it. Right. And the idea that you are now the market maker for doctors, some of them have decided to find their own customers. Doctors being on Instagram to find their own customers is like a whole situation over there. Is that putting pressure on your model?

Oliver Karas (19:28)

No, it's actually so Obviously, some doctors didn't like it, and some doctors liked it a lot. And so the interesting thing about marketplaces in general is that sort of the utilization follows a power curve, right? And so, as you may imagine, if you have one flat fee, the people that are on the top end of the power curve, they're getting essentially value for free. So obviously, and the people that are on the low end of that distribution, they don't get enough value. So everyone who was to sort of the left of that distribution of our sort of new price, they love this model. And a lot more like order of magnitude, more doctors are on zocchart today than when we started that. Obviously, some doctors had to pay more. Right. If you were getting 10,000 patients from us a year and we had a $3,000 fee, that's cents per patient, there's no way you're getting that anywhere, including Instagram. But also obviously, it's now that we ask you to pay a fee per patient, it's going to be a lot more. So clearly there was some adjustment. What is super interesting is that despite the fact that we had to have conversations, oh, your price is going up 100x, which if you ever had that conversation like that, it's not fun. But all of these doctors, all the big spenders actually came back to doctor, except for one, and they came back with us and said, the quality of the patients I'm getting, the volume I'm getting, the way the predictability for my business is such that there is just no alternative.

Neelai Patel (21:05)

We need to take a quick break.

Interviewer / Host (21:06)

We'll be right back.

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Neelai Patel (24:28)

We're back with Zocdoc CEO Oliver Karas talking about the intersection of AI and healthcare and what it means now that chatbots and AI assistants are part of how people seek out and receive medical care.

Interviewer / Host (24:42)

So when you think about that kind of like patient matching again, I look broadly at the industry and I think, okay, well, Meta's thesis is that AI will help us target ads better. Google's thesis, they're less loud about it. But their thesis is that the AI will help them target ads better. That's fundamentally what you're doing. You're matching customers and providers in a real way. Are you employing AI there as well?

Oliver Karas (25:06)

Yes. For the matching process? Absolutely. Yes, we do that.

Interviewer / Host (25:10)

What are the parameters there?

Oliver Karas (25:11)

So we understand a lot about the patients and obviously they also answer questions for us, and we understand a lot about the doctors. There's in some ways, layers of information that are not broadly documented. Really. These are things that we know between the doctors and zocdoc, between the patients and zocdoc, and that's the information we can use to make that match as efficiently as possible. And there's a lot of just public information also that you need to take into account for that. Which doctor accepts your insurance card? Which doctor actually accepts new patients? What type of patients does this doctor see? How long does a doctor typically take for a patient with your chief complaint? And how many do they see them in the morning, do they see them in the afternoon? How many of those can they see consecutively, et cetera? So these are all meta information that we have about the doctor and we have the direct connection to their schedules to see. Okay. Given that those are all the rules, which slots are even potentially available for you. And then obviously there's sort of clinical fitness questions which we tackle. And actually is, I think, a very, very interesting area of growth for us.

Interviewer / Host (26:18)

So the reason I ask these questions this way is that's the heart of ZOC talk. Right. Every one of these referrals now, because you've made the business model change, is revenue for you. And especially if the patient shows up, everyone's very happy. You have to make an investment into making that matching process better. And the investment here is an investment into AI, which is in its early stages. We were talking before. The return on these investments is somewhat unknown. How did you decide? Okay, I'm going to make the forward investment to put AI into our functional teams on the thesis that the matches will become more correct, that the doctors will be happier and the patients will be happier.

Oliver Karas (26:57)

Yeah. So, first of all, we are not making referrals. The patients are using us to book with their doctors. But within the scope of that, from day one, from day one, the challenge was how do you make this match better? Right. And for anyone who is doing business in the actual physical world, understanding all the outliers and all the ways in which this can be off is a critical piece. Because if you apply the 8020 rule, you're going to piss off 20% of your customers. And you cannot do that very often. So you constantly need to sort of zoom in and say, okay, great. What are the remaining edge cases where this doesn't truly work? And this is a problem that's a little bit like the coastline of England, right? Like, if you look at it from a map, it seems like, oh, I can just trace this and I can measure that. But as you zoom in and you say, oh, but here's like a little bay. So I really, like. It's really going in there. And in the bay is a rock, and so there's like another surface and in the rock there's a crack, and then I go to the crack and there are micro cracks. And, like, the smaller you go in and measure, the more you realize, oh, God, I will never be done with that like this. There's just too much to do. Now, AI is great because we can accelerate, like, the kinds of problems that we can solve to make this an ever more seamless experience for the patient and for the doctor.

Interviewer / Host (28:12)

But you had to make an investment, right? You have a functional team, you're building one product together against one number to say, okay, we're going to make this investment into AI. Presumably you had some goals here and the goal was, I know you're not calling them referrals, but the goal is for more patients to work with more doctors. How did you decide that it was worth it?

Oliver Karas (28:31)

So we had a team on that since day one. Except that obviously back in 2007, they were not using AI, but we were using machine learning and other techniques to improve the quality of the match. So we have a belief, actually, that the quality of the match is a huge determinant. We're not trying to optimize the number of bookings in any given moment. We're trying to optimize the experience that the user has, because we believe that's a determinant of do they come back and use us again? Do they have a preference for zocdoc? Because that's the tool that just works.

Interviewer / Host (29:04)

So have you seen it pay off? Have you seen the return on the investment?

Oliver Karas (29:09)

18 years later, we're still here.

Interviewer / Host (29:10)

Well, no, on AI specifically. On Zocdoc, yeah. But on AI specifically, yes, absolutely.

Oliver Karas (29:14)

So I think there too, we're thinking about ways how to use AI to not just make what we have already been doing or what has already been done more efficient, but what new things are now possible that AI exists that were just not possible before. And so there's interesting things coming out in the future, and I'm happy to chat when we're ready to announce them.

Interviewer / Host (29:38)

Let me ask you the other decoder question and I want to ask you about some of these interesting things. How do you make decisions? What's your framework?

Oliver Karas (29:44)

So I am not in founder mode, if that's the question. I actually think I only make, like three types of decisions. The first one is who are the people that I trust and I bring on the bus, right? So what's the senior leadership team? And like, what do I like? Who do I think can actually help us get us to that next milestone? And once I have these people in place, if I chose well, they should know their area better than I ever could. Right? If I hire enterprise sales executive, if I have to teach them how to do their job, I mishired, right? So this needs to be on autopilot. And the only way that can happen is if I don't get into their hair. The second type of decision is where risk is involved. I think organizations, they tend to drive people to take not enough risk. And that is something that as a founder, you're uniquely positioned to say, you know what, I'm going to absorb all the blame if this doesn't go right. You could say, I instructed you to do that. And if it does go right, it's all yours. You came up with it. Go forward. This is when I see that there are areas where we should be taking risk. I get involved and I make sure that everyone knows that there is absolute license to take the risk if it's a smart one. We are not trying to jump off buildings, but there's a lot of opportunity there. The third type of decision is really, when it comes to where's the puck going, this is a thing where you need to integrate a lot of different inputs, right? That there's obviously what's technically feasible then also, I talk a lot to our customers. I understand how they are thinking about the world where they sort of have pebbles in their shoe. And then I spend a lot of time in D.C. and I understand, okay, what does the regulator want? Right? And then you need to triangulate all these things and say, okay, great. Given that, like, what do we need to do? What new capabilities do we need to bring in house to be able to manage that next challenge? And I'm a believer that companies can evolve and develop new capabilities. I don't think core capabilities are boxing you in in any way, but you need to know what you want and what you need. Otherwise you can build it with confidence.

Interviewer / Host (31:58)

Let me put some stress on where the puck is going. So Zoc Talk is a service provider again of a generation of apps where consumers open the phone. They took some control of what you might think of as back office functions. Right. I'm going to book a car, I'm going to find a doctor. Those service providers all expanded in different ways, vertically, horizontally. You have businesses. Yesterday, OpenAI had Dev Day. Anthropic was just on stage. They introduced MCP. The idea that the AIs are going to disintermediate service providers feels very real. I call this the DoorDash problem. If I say, alexa, order me a sandwich and it goes and clicks around on the DoorDash website and the sandwich shows up, DoorDash might be out of business, right? Because all of the revenue that's associated with me actually using DoorDash will go away and they will become a commodity provider of sandwiches, which is not a great business to be in. That might happen to you, right? I might say, alexa, find me a doctor and it might go traverse the ZOCDOC backend and take you out of it. Right? And all these new capabilities you want to build might be disintermediated. Are you thinking about that? Are you thinking that you want to integrate with these new kinds of agents or are you going to try to build them yourself?

Oliver Karas (33:06)

So we'll integrate with these agents. And the reason is that I think that fear, the doordash fear, might be slightly flawed thinking. And here's why I think that. Here are the questions you should ask yourself. Question number one, Are these agents simply going to completely displace yourself? Right. Anyone who is running a business that interacts with the real world knows that that's not going to be the case because of that learning curve, because of all the edge cases, all these things, Even if the AIs were to start learning about them, we're so much further ahead. We can always deliver a better experience. So this is the coast of England problem. Our cartographers have been at this for 20 years. There's no way that anyone will catch up to us anytime soon. So they're not going to put us out of business. Now the second question is, are they going to drain the profit pools for these things? So you could say, well, there's a world where you could imagine this happening, where consumers pay a subscription fee to people that build these agents and then the agents find the optimal price for you. That flies in the face of the entire monetization model of the Internet, if you look at it, everything has been monetized through advertising. And so you'd have to believe that there's going to be an anthropological change where people suddenly say, yeah, I'm actually happy to pay upfront and then maybe like collect rewards over time, where this is potentially giving me better deals. But if that were true, like everyone would be eating healthy, working out, taking all preventative tests, etc. So we just think, I just think that that is not how humans actually work. And so then the third thing is, okay, fine, the profit pools will not be completely drained, but are they going to take most of my profits away? I think there we are all anchored in these last 20 plus years where Google was a monopolist and could ask for these tolls. I think the tables have actually very much turned. There's five major LLMs or AI companies that are competing to be your agent. Imagine you had the one that doesn't let you order a sandwich, that doesn't let you book an Airbnb, that doesn't let you call an Uber, that doesn't let you book a doctor. Would you use that one? No. And so the providers of these services actually have a lot of leverage right now to sort of negotiate the kinds of relationship with these AI agents that they never had with Google because Google was already the monopolist when they came up.

Interviewer / Host (35:44)

Well, okay, there's a lot in that answer, but I actually want to focus on that last piece for one second, where the leverage comes from. I think there's a lot of leverage if everyone agrees that MCP is the way this is going to work, right? And then you can say, my MCP server is open to Amazon and Google but closed to Microsoft or however this plays out. And then now we're just negotiating, we're just negotiating API access with a different set of vocabulary. I look at some of these companies and they say, well, screw it, we're just going to go click around on your website, we're just going to open a browser and we're going to click the buttons for the user and we'll do that in the background. And you might never know, you might never know that this happened. Perplexity is going to do a browser. Knowing Perplexity, that is probably how their agent will work. That destroys your leverage. You have to detect their agent and say, you can't do automated browsing. And there's no framework, there's no negotiation framework for that.

Oliver Karas (36:38)

So why they do that? Right? They are not making any money. And I make money as I Used to. So that's actually cool.

Interviewer / Host (36:44)

Give me your advertising money.

Oliver Karas (36:47)

Well, who? How do you know? Because I might know.

Interviewer / Host (36:50)

Which I agree that Internet advertising is rife with automated fraud, but, like, that's not the right answer.

Oliver Karas (36:54)

Let's look at Uber, right? Like, Uber is making money from the driver that was the model, Right. Uber would be getting all that free traffic from Perplexity. I'm sure they love that. And I'm sure Airbnb, if you book through Perplexity and no money flows to Perplexity, I'm sure Airbnb will love that. Like DoorDash. Oh, you order through my DoorDash app and I don't have to pay you for traffic. Great. Like, why wouldn't people want that?

Interviewer / Host (37:20)

But. So this is the other outcome, right? There's the let's negotiate MCP access on the front end and have revenue share. And then there's the bet that automated browsing will bring so much traffic or money and there won't be negotiations, but it all work out. And that's the split I see right now. Right? There's more heat in browser coverage as a tech journalist than there's been in over a decade because people want to build new kinds of browsers that take action for the user. And then there's a lot of heat on mcp.

Oliver Karas (37:50)

Yeah, but if you look at the companies that create the most value, right, they are not trying to do this through pure advertising. Right? Like, obviously, advertising is a part of everyone's revenue, but they take you transaction fees, right? You order that sandwich, you pay a service fee to Doordash. Right? You book this Airbnb, they're taking a cut on the booking fee from you. So, yeah, use the website, right? That is a totally fine mechanism. And if less money, I mean, Airbnb doesn't even have advertising, but if less money comes in through advertising, you'll take that right back in other ways. So I don't think there's really a threat there. And if they are going to negotiate, if they do want to have some of that money, I think these companies that are the Ubers, the Airbnbs, the Doordash of this world, are in a unique position to dictate their terms in a way that they could never do with Google.

Interviewer / Host (38:44)

Well, Google's a really interesting case. Right. And Google also owns a browser. It seems like Chrome is going to be automated in a lot of way. Google also is the search engine of record. Do you feel yourself in a position to negotiate with Google differently than every other kind of vertical search engine has in the past right now, look, I.

Oliver Karas (39:01)

Think we are always looking to help patients wherever they are, in whatever way they want to interact with us. Like, we even work with health insurance companies where ZocDoc is completely hidden. You log in with your health insurance company login, you see the doctors that are in network with your health insurance. You book one, you use the Zoc talk pipes. But you know, as sort of the patient, as the member of that insurance company, you, you don't need.

Interviewer / Host (39:29)

Let me ask this slightly different. If you went to Google today, right, and said, look, people are going to talk to Gemini instead of the Google search box when they look for a doctor, just have Gemini use our pipes and pay us for it. Is that a. A year ago, two years ago, the door wouldn't have even been open. You would have just been at the door of Mountain View saying, use our pipes, pay us money, and they would have not paid any attention to you. Do you have the leverage to open that door today?

Oliver Karas (39:52)

I think these doors are more open than ever. That's exactly right. And I think as Gemini is trying to be your AI agent and ChatGPT and Grok and Propaxity and Claude to some degree, right? Well, do you want to be the chat agent that uniquely doesn't have the capability to use Uber's pipes, doordash pipes, doctor's pipes. Like that would put you at a competitive disadvantage. And I think that is sort of a reality that all these companies have to grapple with. No one more than Google, who has.

Interviewer / Host (40:23)

Historically enjoyed this monopoly, who is zocdoc's biggest competitor.

Oliver Karas (40:28)

So there's obviously still a lot of.

Interviewer / Host (40:30)

Like, head up, like when you're like, I got to. We got to beat those guys. Who is it?

Oliver Karas (40:33)

So in terms of our core marketplace, it is such a difficult business that, you know, competitive waves have come and gone. Right now there aren't necessarily.

Interviewer / Host (40:44)

But this is why you're special, right? I mean, I asked that for a reason. If Google or ChatGPT or perplexity wants to get a doctor for you, they have to come talk to you, right? In a very direct way. You are the database of record for that thing. If you're doordash. Well, Uber Eats exists, right? Like, there are many other ways to do this. And I'm kind of wondering if you see the opportunity for one of your tangential or orthogonal competitors to say, actually we have a database of doctors too. We just never built the front end to let patients book directly. But your agent can come use our database and do it for them. And now this is a new kind of threat for you.

Oliver Karas (41:23)

So I think, again, their cartography problem, right, the coast of England problem is, I think, the reason why there are no other ships sailing in our direction. Right? Because you need to be very patient. And we literally, we did not leave New York for four years just to make sure that we get even to a base level of this functioning. Because there is the technology problem of integrating with all these EHRs, but then there's an anthropology problem on top of this. How do these practice managers and front office folks, how do they actually use these EHRs? Right? And what's the hidden information that you cannot extract from electronic systems? And we've gone through all of that and we have learned it the hard way over many years, and we've continued to learn it for two decades. So could you start a zoctor competitor today? Of course you could. Right. Would it be a dramatically worse experience than using zocdoc? Yeah, it would be. Right. And so this is why I think that these AI agents will want to work with someone like us who can deliver a great experience for their users.

Interviewer / Host (42:25)

I would say, at least in the case of OpenAI, what ChatGPT has proven is like, oh, we'll take anything. Like this robot will tell me I'm in love with it. And that's better. That might be better than a real relationship. And that kind of disruption is real here. Right. It will do the job slightly worse, but it's doing the job in this interface is the kind of disruption I think, not just ZocDoc, but the whole industry is facing. I'm just not sure.

Oliver Karas (42:47)

I think that is going to be great until you try to catch your flight and the Uber didn't show up, that you'd got to chatgpt, right, or you're hungry. All the restaurants are now closed. It turns out your daughter's order didn't go through. You're arriving in Miami and your Airbnb is occupied by someone else. How often can you do that? It's very different from telling you, oh, I love you, that works. It's probably true. But even if it wasn't true, we have fewer expectations about how these communication challenges resolve versus things that happen in the real world. Right. And this is where I think the experience Head Start that all these operators in the real world have compared to a chatgpt is going to be a sustainable advantage.

Neelai Patel (43:37)

We need to take another quick break. We'll be right back.

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Neelai Patel (47:34)

Foreign we're back with zocdoc CEO Oliver Karaz. We've spent a lot of time in this conversation discussing the technical side of AI and medicine, but now I wanted to ask Oliver about the complicated state of healthcare in America and how his position as the CEO of the largest platform for doctors might give him a unique perspective on what the future of that system looks like.

Interviewer / Host (48:00)

I do feel like we should spend the last 20 minutes here talking about the stakes of saying I love you versus the stakes of booking a flight.

Oliver Karas (48:05)

I love that. Why not the idea that the stakes.

Interviewer / Host (48:07)

Of saying I love you are lower than missing a flight. I do feel like we need more than 20 minutes for that. There's a lot to say about the AI conversation right in that idea. There's one more platform I want to talk about and I want to talk to some other things specifically about healthcare. Apple Apple announced Siri with app intents that was going to be this high powered assistant. I think a lot of people assumed that they would have a huge head start because all the apps are already on the phone. There's already some hooks into automating apps on the phone in various ways. That seemed like a bit of a false start. They recently made some noises about mcp, which is kind of wild, right? For Apple, it's the owner of iOS to say MCP might be the way they go. Would you allow Siri on the phone to use your app in an automated way? Because that also seems like a disintermediation.

Oliver Karas (48:55)

For the same reason that I allow Asians at the Veterans Administration or care coordinators at Blue Shield of California to use the app in an unbranded way? I would absolutely allow Siri to do that.

Interviewer / Host (49:10)

Would you expect it to actually open your app and click around? Or would you just expose the database and the service of your app to Siri?

Oliver Karas (49:16)

We'd obviously have to explore more what consumers really want. But I'm very open to finding a path that is optimal for the patient. Right. That's why we ultimately exist. And that's a completely orthogonal topic to what's the relationship between Siri and zocdoc going to be? Right?

Interviewer / Host (49:34)

App developers have had a, I would say bumpy relationship with Apple over the past few years. In the same way you're describing the doors are open at Google. Do you feel like the doors are open to have different kinds of relationship with Apple now?

Oliver Karas (49:46)

I mean, we are really into win wins and that's why we have always had great relationships with everyone. I can remember being at war with any of those guys and we were very focused on the things that we really want to do and want to do really, really well. And sometimes that overlaps with what someone else wants. And then you can say I love you and sometimes it doesn't. And then we both like stay friends and go our own ways. And I think those conversations will be ongoing. And I think it's a very quickly evolving space where even folks like Apple will have to rethink how they are approaching the optimal solution for their users.

Interviewer / Host (50:25)

Are you making the same bet on MCP as everyone else or are you more agnostic about how these agents will work?

Oliver Karas (50:30)

Look, I think there's. You should just try out a bunch of things. It's not well known at this point how these agents will be structured in a way that really gives the patient confidence or the user confidence rather, and leads to them using them correctly. Now I will say that sometimes complex information, we've played around with it, and sometimes you want visual feedback because you can just convey a lot more of it in one glance and talking you through all your options, et cetera. So I think there's. It's going to be evolving paradigms for simple things where I can just tell you, hey, order me toothpaste versus oh, give me my options to do xyz. And now the options need to be arranged in a way that I can take that information in quickly. It's like the narrative of it will be maybe too much for me. And so I think this will evolve. But we are there for it and we're happy to partner with anyone who's interested in making this better.

Interviewer / Host (51:25)

One of the reasons I wanted to ask you that specifically is the criticism of MCP is that it has an enormous number of security issues with it. It's going to expose a lot of data. You have just API access to database in Non deterministic ways. You don't really know how both sides of the transaction will work. In healthcare. You have an obligation to the patient, to the government or the provider to keep so much information private. Do you think MCP is compatible with your business?

Oliver Karas (51:52)

Look, I won't opine on the technical constraints that you have to put in. All I can say is that we use AI in some arenas where it's critical that you get to the right results, that what you do is unit testable. And we have managed to put frameworks in place that give us complete confidence that we're not hallucinating, that we're not going out of bounds of what is allowable. And this is sort of that hybrid framework between deterministic parts of the application and LLM based ones. And I think we'll have to figure out how that actually works in the future to make sure that we continue to put that safety and the safety of the data first and we don't create unforeseen results for the end users. Right, but that is, I just take this as a given and I think that's something that we can invent around and still come to good results.

Interviewer / Host (52:45)

Well, so you mentioned this sort of hybrid approach to development at the top of conversation and I want to spend a minute on it here. The bet, you know, all the money in AI is that the AI will eat everything, right? This is the way computers are going to work, this is the way we're going to write applications, this is the way that programs will talk to each other, this is the way the services interact. And all this will happen in the context of AI, like specifically LLMs and mcp. That's the future of everything. That's a bet that is supporting a lot of investment right now that everything will eventually operate in this framework. You are describing a very different framework, Right. You're saying I need to surround these models with traditional deterministic algorithms and systems that guarantee the results I need. And this is actually the future for our business. That's not the prevailing bet. That's not how the investment will pay off for all the massive investment. But it's very. Having talked to you about it, you seem very confident in that way of working. Do you think there's a path for the AI, the AI systems as they're being developed now, to actually do the job as well as the hybrid model that you're describing?

Oliver Karas (53:47)

So not today. Yeah, not today. Right. And is there a path for it to get there over time? People smarter than me are investing hundreds of Billions of dollars into that.

Interviewer / Host (53:56)

So are they smarter than you? For sure.

Oliver Karas (53:59)

Like that is like the one sure thing to say. But they're investing a lot of money in that. And I think there is probably a belief that would justify that money that we can get to AGI and maybe that will happen tomorrow. I think as an observer of the scene, I would say that's probably less likely. Right. Like we just had the release of Sora. Like, if you were, you know, expecting AGI in the near term, would you really invest in a video editing tool? No, you'd be working towards AGI. So I think we're probably many, many years away from reaching this point in actuality, which gives us enough time to learn which elements of that are useful in which situation and in life. The answer is nearly always. It depends. For some tasks, obviously the LLMs as they come out of the box today are just wonderful. For some tasks, you can't trust them enough and you need to put them into an orchestration layer. And I think we'll see how that evolves. But I cannot imagine a world where everything is is one thing, because as we talked about earlier, we're still making 86 chips, right? And they were in when, when I was a kid, 40 years ago.

Interviewer / Host (55:15)

And now the United States government is in the business of making 8086 chips, which is real, a real mindbender. Let's actually go there to wrap it up. Health care is a deeply regulated space. Healthcare in America is under threat. We're talking in the middle of a government shutdown. That shutdown hinges on the future of the aca, for example, and how those payments might work. Zocdoc exists because people have to go to the doctor in many cases because they have an insurance provider. And that first filter is just finding a doctor who will take my insurance. Obviously, the market is under an enormous amount of pressure and stress right now. What are you seeing is the maker of the market in response to that?

Oliver Karas (55:54)

Yeah. So look, what is sort of the secret behind zoctruck and the contrarian insight is actually that doctors are not as busy as it seems. Right. Doctors have roughly 30% spare capacity. That comes from last minute cancellations, no shows, reschedules. And as doctors are put under pressure because of the current budget disputes and sort of reallocations of funds, it becomes more and more pressing for them to actually utilize these last 30%. And so they can tend to use ZocDoc more than they maybe did before. And obviously we're in the business of helping patients and doctors connected. So we're happy to sort of fill in the breach here for the doctors and make sure they stay viable businesses broadly. Right. Like our ambition is to realize the full potential of a marketplace which means you can improve access, quality and cost. Right. We started with access because it was the most broken thing and it was also our way to sort of get to enough scale to focus on these other problems in the future. But these are very much near and dear to our heart. And we want to be a true market maker that helps patients find cost efficient care of high quality that they can actually use.

Interviewer / Host (57:12)

So cost efficient. Right. That's the thing that's under pressure right now. Will the ACA subsidies across the country survive in various ways? Obviously that's like deeply political. But one outcome here is one potential outcome here is that those subsidies go away and costs skyrocket and some providers have to go out of business. Is that something that you're prepared for, that customers are going to open ZOCDOC and look for providers that aren't there or you might have to find them cheaper?

Oliver Karas (57:39)

I don't think that that is going to happen in that way. And simply look back into the times before the ACA was around. Right?

Interviewer / Host (57:47)

Yeah.

Oliver Karas (57:48)

There were more uninsured patients and ultimately we still treated them. Right? We still treat them, but it was uncompensated care. The doctors made up for that by charging the patients that had commercial insurance more money. Right. And so as we sort of migrated uncompensated care into the aca, the overall increase in rates maybe slowed down a little bit versus what it would have done. Hard to say because there's no counterfactual here, but that is one way to look at it. We're not actually lowering the total expenditure of care. The only way how you could do that is by saying no. Not only are we locking people out of Medicaid or the aca, we're also preventing them receiving treatment. And I haven't really heard anyone say that yet because that has very dramatic implications on how we understand ourselves as a society that has solidarity with other citizens of this country that are not as fortunate as we are, either from a health perspective or from an affluence perspective. And so that's a completely separate political debate that hasn't even been had yet.

Interviewer / Host (59:01)

I would say broadly, a criticism of the entire health care system in America, asay or not, is that it has become commercialized. Right. It is more market driven than idealistically driven. As you're describing, my whole family is doctors, they have a lot of thoughts about this. But the idea that there's not actually price transparency in this very commercialized healthcare system. The prices are often locked away or pre negotiated and you get a lot of bills that don't make any sense. All that's very true for people. It's very frustrating as the market maker if the system becomes even more commercialized. Right. If we start to move these numbers around because the regulatory framework has changed, would you put price transparency into zoctoc and say this is how much these doctors cost?

Oliver Karas (59:45)

Yeah. So at the right time, the answer is yes. The way that we understand ourselves is actually in some ways is a union of all the patients that are using ZOC and we're using their collective purchasing power to start affecting change in the system. And we have seen providers being quite responsive. Right. We say, oh, patients really would like to see you earlier in the morning or later in the evening and they need insight into certain elements of what you're doing and what you might be charging. So this is where the existence of zoctruck is. A marketplace that's bundling decisions of millions and millions and millions of patients is actually a catalyst to the type of change that we want to see. And I think it's very different from how the government is trying to affect this change because we have regulation in place that says that payers and hospitals need to publish their prices, but that regulation is punitive. If you don't, I'm going to fine you. And whenever you do that, you have all the smartest people in these organizations trying to figure out how to obey with the letter of the law. But circumvent the spirit. Right. Whereas Dr. Can actually reward you for the right behavior. Hey, if you do give the patient more information, well, maybe you're listed in a more prominent spot on the marketplace. And therefore now they have all the smartest people working on, well, how can we give ZOCDOC the information they need to make this better for the patient? And so this is, I think, the eternal optimist in me thinking that yes, we can build a better system. It's not going to be instantaneous. It's unfortunately not affaired by the government, but it is something that we can build from the bottom up.

Interviewer / Host (61:18)

I like that you described it as a union of consumers. I mean, that is just another way of saying you have a lot of demand and you can apply it to the market in focused ways. That said, I would not say most health care consumers in America are thrilled. They don't seem all that happy. No one seems happy with the system as it's currently designed. When you think about the leverage ZocDoc has with the aggregate demand that you have on your platform, where are the most effective places for you to apply that pressure to make change such that people are actually happier?

Oliver Karas (61:49)

So we are already doing that today. We're working with the Veterans Administration. It used to be many, many weeks for a veteran to get access to a provider. We have cut that down to just a few days. Same is true with Blue Shield of California, where we have, you know, given people access much more quickly to more, you know, specific doctors that are better for their actual conditions. So we are sort of starting to grind away at this. We are firm believers that you can come into health care and say, if the system, you know, we're tearing it all down and we're building, you know, new. This is, you know, a multitrillion dollar deployed assets in healthcare, right? You have to improve it from the bottom up and work with the institutions that are really doing their best in many ways to try and help patients, but they just don't have the technology layer necessarily, and they can't overcome the collective action problem on their own, and they need a facilitator like ZocDoc to get there.

Interviewer / Host (62:47)

You're describing the Veterans Administration. You're describing the state of California. Those are large government entities, some of the largest that exist. Is the government more responsive to tech solutions because of AI? Lately I listened to this administration, and basically they're like, the AI will do it, right? Like, the promise of DOGE is like, the AI will just. AI will do everything. I don't think that was true. I don't think that worked out. But there's a different attitude that I hear from so many people in tech about this administration. Their willingness to adopt new tools, or at least their faith that the new tools can lower costs in some way has that borne out for you.

Oliver Karas (63:25)

So, look, as an entrepreneur, I obviously love interacting with optimists, right? So anyone who thinks that the world can change and can be better, I love dealing with. But as OkToc, we have worked with five administrations over the years. We have always had good bipartisan relationships, and we are really on the side of the patient more than anyone else. And we'll work with anyone who is trying to come up with better solutions for Americans.

Interviewer / Host (63:52)

When you think about the biggest request from that patient base that you have on the platform right now, what's the number one thing that they want that you can't quite give them yet.

Oliver Karas (64:00)

We are still catographing. So the reality is that healthcare is incredibly complex. We'll forever be busy to make just the simple thing that we do today even better and make sure that we meet you with more doctors to choose from that are more specialized for what you do. But I think what the journey that we're on right now is to make sure that you don't have to come to zocdoc to experience that. Right. Like wherever you are, we will meet you there and we'll start sort of making this better for you with the same convenience that you're experiencing on zocdoc. And then to the extent that you have to take these steps that are offline, calling the doctor's office. Right. We want to make that experience better for you as well. So we are really trying to be an all round for you as the patient that makes every interaction with the US healthcare system better for you, whether you know that Sockdoc inside or not.

Interviewer / Host (64:56)

When you think about that overall experience, I think this is, it's kind of where we started. It's where I want to wrap up. The idea that you could expand into the actual provision of healthcare is kind of right in front of you, right where you have a patient, you know, they're specialists, you know, they're doctors, they might tell you some symptoms, you might know who's available and then they might ask you for that last twist of advice, right? My knee hurts. What can I do for my knee? And right now ZocDoc won't do that, but ChatGPT certainly will. It'll just give you medical advice. It'll say it shouldn't sometimes, but mostly it'll just do it. Right. Is that a threat, that last turn, or is that something you want to expand into?

Oliver Karas (65:35)

So I think Dr. Google has been around since before ZocDoc was launched and there's obviously going to be some comfort level that patients have to ask ChatGPT or Dr. Google for advice.

Interviewer / Host (65:47)

Can I just make the distinction just a little more sharply? Dr. Google? My family hates Dr. Google. Again, they're all doctors, but at least Dr. Google is dropping you on the Cleveland Clinic website. It's like, here's some stuff from this reputable organization and it's all bracketed with talk to doctors. ChatGPT is like, here's some answers. Go get this drug from your doctor. Very different set of authorities, very different set of symbols, very different experience. That's going to change something. Is that the threat?

Oliver Karas (66:19)

So I think we haven't really seen the full cycle of that. I think people will do that and sometimes will have great experiences and sometimes they will have not so great experiences. And then over time norms will develop. When you actually let ChatGPT stand in for Dr. Google and when you actually want to talk to a human being. I don't know that we know the surface area right now and obviously, like, look, ultimately it's a free country. We're all adults. Like, I have my own judgment where I would let LLMs inform me. And I think there's a lot of things that you can get extremely well out of LLMs today that can help you actually structure your conversation with the doctor in a way that you get everything out of that you could. So I think there's definitely a lot of upside where the exact boundaries are. I think experience will show and it's a little bit like when you go to college, like how much should you drink? You'll figure it out over the course of four years.

Interviewer / Host (67:17)

Yeah. Where's the boundary in ZOCDOC today?

Oliver Karas (67:19)

We don't give medical advice and that's.

Interviewer / Host (67:22)

Going to stay firm until something else changes.

Oliver Karas (67:24)

Yes.

Interviewer / Host (67:25)

What would make you change it?

Oliver Karas (67:29)

We really have to find defined buckets where we know that the LLM or the AI knows what it doesn't know and it knows when it has sort of a curiosity gap. And the stakes of the advice are low enough. Right. These are two way doors. Okay. Worst case, your headache takes another three hours.

Interviewer / Host (67:52)

Great.

Oliver Karas (67:53)

Maybe that's a risk you could take. Whether you should take a medication that has far reaching and long term effects. I think I'd be very, very hesitant to do that outside of a human in the loop at this point. And then I don't, obviously you could stipulate, okay, AGI is going to solve all of that. I think that's a totally different discussion altogether when we say, okay, humans are going to be broadly obsolete. I happen to think that will happen in medicine as one of the last bastions because we have all the physicality of our body that needs to be examined and we have so many degrees of freedom in how we live our lives that bring surprising twists to the body of knowledge that I think doctors have a pretty safe future.

Interviewer / Host (68:42)

Yeah. I just think the other side of that is deep. Fake Sam Altman is like, take drugs and like, I don't know how that's going to play out. Last question then we got to wrap it up. It's an easy one. Do you think this is a bubble?

Oliver Karas (68:54)

I mean, if I knew that I could make a lot more money on the stock market than sitting here. I think there's always a risk. I think it's a big bet. And as bets go, they can go in two directions. I think this is also one of those that could go in either direction. I think more and more people have come questioned more recently whether this is going in the right direction. I think in either scenario, AI is a useful technology that will endure. Whether we're paying the right prices for certain assets right now, who am I to judge?

Interviewer / Host (69:30)

Well, Oliver, this has been a great conversation. We got to catch up again soon. Thank you for being on Decoder, Eli.

Oliver Karas (69:35)

Thank you.

Interviewer / Host (69:39)

I'd like to thank all of our.

Neelai Patel (69:40)

Crowds for taking the time to speak with me, and thank you for listening. I hope you enjoyed it. I'm excited to be back.

Interviewer / Host (69:45)

If you'd like to let us know.

Neelai Patel (69:46)

What you thought about this episode or really anything else, you can drop us a line. You can email us atdecoder the verge.com we really do read all the emails. Or you can hit me up directly on threads or Blue Sky. We also have a TikTok and Instagram and now a YouTube channel. You can check all those out at Decoder Pod and they're going to be a lot of fun. If you like Decoder, please share it with your friends and subscribe wherever you get your podcasts. And as a reminder, paid subscribers to the Verge can now listen to Decoder version history and the vergecast completely ad free. Just head to your account settings page to opt in and start listing without ads. If you're not a member, you can go to theverge.com subscribe to get ad free podcasts plus other perks like exclusive newsletters and unlimited access to everything we publish. Actually, on that note, we're coming up on a year since we launched the Verge subscription and we want to hear from you. Take our quick survey@theverge.com survey and tell us what you think. Think Decoder is a production of the Verge and part of the Vox Media Podcast Network. Our producers are Kate Cox and Nick Statt. This episode was edited by Ursa Wright and Chris Jariza. The decoder music is by Breakmaster Cylinder. We'll see you next time.