Building a guardian angel for physicians - Vera Health

Hey everyone, welcome back to the Medical Innovation Podcast. My name is Bruno, I'm here with my co-host, Arvind. Today I'm speaking with two really interesting founders and innovators in the health tech space, Maxime and Tayeb of Vera Health. We've had a chance at connecting with them before and they're both really fascinating, and have a really great story to tell, so we're excited to share their perspective and their journey with you guys. My name, Tayeb, would you mind starting off by sharing a little bit about yourselves and your backgrounds? Yeah, of course, super excited to tell you more about Vera and about our personal backgrounds. So yeah, I'm Tayeb, one of the two co-founders of Vera Health. Maxime, I can let you introduce yourself quickly. For sure, thank you for having us on the podcast. I'm Maxime, I come from France, born and raised in Paris. I started studying business in a school at HCC in Paris and then I transitioned into technology. So in Paris, which is C, I did a Masters in Applied Math and in AI, I'd sort of gone to Paris as well. And then I went on to do final finish my studies at MIT in the science with a lot of classes in healthcare. So most of my studies have been the intersection of the science and healthcare, and that's where I got to meet Tayeb. And on my end, I started studying biomedical engineering and bioinformatics at CHEL before meeting Maxime last year at MIT. We both come from familiar physicians. We both, we both immerse in that healthcare field, both passionate by the healthcare and AI and how we can apply AI and the best and most safe way possible in the healthcare industry. The funny story of Max and I and the first time we met was last year at MIT when we first had that coffee in Cambridge. And I was telling Maxime about the fact that I was building some predictive model for my father who was a retinologist. And I was telling him about how I was trying to optimize some deep learning methods to quantify the number of hemorrhages and exudate some fungic images. And usually when I start talking about that, people get bored. And Maxime was telling me that he was doing the exact same thing at the same time for his father's specialty. And that's how we bonded there. That's how we started working together with so many hackathons. We just realized how efficient we are as a team. And we've experienced firsthand some of the issues that our parents were facing as physicians. And that's why we started their own health. Yeah, it's incredible. It's how unique to both have the same background and come together in that moment to build that. Just hearing a little bit more about your both mutual interests in healthcare, did that kind of stem from the family relations of people that you saw in your life that were in healthcare or anything else that kind of really inspired you to build in this space. And particularly with Vera, what inspired that particular example of building in healthcare? Yeah, it's a combination of many things. On my end, growing up in a family of physicians definitely helped. I've also always wanted to become an entrepreneur and become an entrepreneur in something that could have an impact and a true impact for people. So a lot of synergies between my personal background and the family have been raised in and what to have an impact in a way or another. So yeah, I think that it was pretty natural for me to dig a bit more into the healthcare space. And maybe on my side, growing up in the country where we have social security and we have pre-access to healthcare, coming to the US, you realize that you took for granted having an access to a healthcare that is quite efficient in France. And so I think it's also quite interesting to apply some of the learnings that we have back in France and in Europe to the US healthcare system. Yeah, that makes a lot of sense. Going back to your earlier point about how you guys came together because you were working on very similar projects for each of your respective fathers, I'm curious how that evolved into you guys working together and building Vera Health. When you first started building, what did it look like? What was your vision of what Vera would become? Interesting question. Initially, before we were building a different solution, so maximum is an athlete. And I've always been into kind of the longevity side of things we've seen how AI and healthcare have made things easier for a lot of people and we wanted at first to build a consumer app. So that was the initial idea, that's what we teach to YC at first. And then we realized the big need of healthcare professionals. And we've seen firsthand our parents struggling coming back home with tons of books to go through a complex case they had during the day. We learned more about up to dates. We downloaded the app, tried it and just realized that we have the ability to now to help physicians have access to the best medical evidence at the point of care to make life easier for them, to help them have access to better information in a matter of seconds when they needed the most. And then we decided to push into that specific space and that specific direction during YC and post-YC. Our mission has always been since the day we applied to YC to try and organize medical knowledge. But then from the day we applied to the day we launched our products by being in July to the product we have now, it's been evolving as we strut ourselves with clinicians. And now we can do afterwards in this but mostly emergency physicians and emergency clinicians. And now we have started ourselves with clinicians. It has evolved into something that is very usable in the clinical sets. Whereas as they have said at the beginning it was more for consumers. So yeah, but the mission has remained the same which is organizing medical knowledge in a way that is digestible for the users. Yeah, that sounds great. And I think the YC factor of that too when you sound like there is maybe a little bit of a pivot or some thoughts about like a different ideas as well. We're always curious about hearing founders experiences through incubators, especially like YC. It sounds like such a unique experience that not many people have but it's exciting, terrifying, just a lot of emotions all at the same time. Would love to hear YL's experience on going through YC whether that's the application process or later. We did see on your website that you were at your graduation during one of the meetings which is kind of iconic. Yeah, would love to hear your journey through that. Yeah, I mean, YC was it's a combination of everything you said. YC was an incredible experience and I think that being able to be surrounded by as many incredible people, people who are truly passionate about what they do just help you, just help to push your boundaries every single day. It was like a funny story but we were renting a flight in a building and we were having in the exact same floor as us. There were like five other YC companies. It was so funny to see that that whole floor was like a huge open space. And we've all been through the same struggles, like maybe a week apart. And every time we had an issue rather from like a tech or like product perspective, we always had like another company who made the exact same issues as us like a week before. We've just been surrounded in that incredible ecosystem where people just work at the same as hell, push their boundaries to every single day and are truly passionate about what they do. So being immersed in that kind of atmosphere was definitely super valuable for us. That's incredible. I mean, I think every YC fan we've talked to has said that it's just a phenomenal experience and uncomfortable to anything else. The idea of having so many calendars around you who are going through similar situations facing similar challenges at similar stages in their companies is just a tremendous value at it. But if you were to think back on your experience and if you were to start from scratch again and go back to day one, what would you have done differently? Would you have approached the, you know, a few months they were there differently? Would you have taken different opportunities? What would you have changed about how you have ran this company or grown this company since YC? That's a great question. That's a tough question as well. I think we made mistakes during YC that we know of and we're really happy that we made them. And there are many things that our partner, so Serbi and Gary were telling us during the tough hours and you would just listen and then do the mistake anyway. And I think that's just the way it goes for everyone. Like, until you have done the thing, you don't believe even if like Gary 10 has seen like thousands of startups, you're not going to believe them until you have been seeing. So I don't, I mean maybe I will have a different answer but on my I don't think there would have been something We've done differently, but there obviously many mistakes with mail and we can discuss them But those were just learning for us Yeah, I totally agree, but that's that's exactly it like the very first day The very first office hour with YC was even before at the start of the batch and I remember Gary saying to all of us We'll tell you some things and we'll decide to not follow them and in a couple of months You'll realize that you are right So I think that if we had to do YC again, we wouldn't do the same mistakes as the one we did But we'd probably do others and we learned from that and Maxine said it's said it in the right way We We wouldn't do it differently now because we learned so much from the own mistakes that we made and that's that's part of the journey And that's part of creating a startup That's funny, but um I guess not surprising People can give you all the console and advice in the world, but at the end of the day you learn the most from your own mistakes You have to fail in order to grow so It totally makes sense why so many founders will make the mistakes despite Gary or you know the rest of the YC team telling them exactly how to avoid those mistakes But could you maybe give an example of mistake you made during your time at YC and What you learn from it? I think maybe um we brought someone in Um too early on and Like it was a wasted advice not to do this and they were like do not bring someone in as early as during the YC batch Especially someone that is senior because you always like okay We're gonna bring in knowledge and experience by bringing someone at a senior to the team and we'll help us on For us it was like some go-to-market Like motion because we're selling to happier systems and large hospitals and we that we don't really know how it's worked and we we didn't know at the time um and so i mean obviously we met the mistake because um what they come in with is all of their 10 years of experience I had to know the firm that is that wasn't a third of it It was actually a huge incandence um So not the same third of the losities as us we want to move at for like when you're during YC Every day Something happens and like i mean many things happen right and it's really tough for someone who is not a founder or a funding engineer or a Finding employee to realize and and go at the same velocity as us So we had to let her go um like three weeks in just because we were definitely not a sentence um Yeah, I think that was the biggest mistake we've made and we knew I think we had this question Say of the day we we hired her and we knew we were making a mistake but we're like this is really not Yeah, and we appreciate your vulnerability and sharing that I feel like um It's it's really insightful to get like the actual You know mistakes that folks have made and to you know make it heard that it's not It's not uncommon for that to happen. So uh we appreciate you sharing that no well I guess go timeline wise right so you go through YC Come out on the other end of it with a really strong product that uh is in the clinical decision support space We would love to hear about Kind of how your product works um what services that you're focusing on currently um and just Yeah, just a basic overview of what Vera Health does and um How it works Yeah, definitely um I think my my sense that it's very well in the beginning Um, we're we are we're trying to organize medical knowledge Um, so we were trying to and I think we we're in a good point right now um the very first product we built at first a lot of synergies from a tech perspective because we always had that um that we all to Make things simpler and being able to help physician access the best medical evidence So we're truly a search engine um and most of our focus since the very early days um of building the product was Creating the most powerful search engine we can in the medical space Um and that comes with a lot of challenges um it goes way beyond doing simple rag Because when you're trying to get the best medical evidence for healthcare providers it goes beyond all the techniques that uh Rad systems could do such as cosine similarity because every piece of evidence has like a different kind of reliability Um like for instance a meta analysis or randomized control trials Uh would be more highly viewed from um from a physician standpoint than like a case report Um you have a journal you have a number of citations you have a publication here you need to make sure that you provide the most recent paper and like taking all of that into accounts Um is extremely hard and uh that was our whole focus since day one making sure that we can bring the latest most relevant piece of evidence From scientific papers or like from a drug that I've been or from a drug database That would help that would help the physician make the best decision at the point of care for his patients um so whole work um uh towards that um and then of course we built a reasoning engine uh around it So uh at a time that we fine tune on scientific knowledge um that we're evaluating constantly to make sure that we always answer just using the relevance that we found um making sure that we don't hallucinate and making sure that we have a robust reasoning engine uh that is grounded on the on the on the database and on the medical evidence that we have Um so that's pretty much all um around the technology we built uh for zero um i'm not even max has anything else to add Yeah um i mean i think you you went to the details so it's quite clear what we do um but there is this phrasing that we that we love that we took from ground alter actually that you will have on the podcast very soon which is like think of Mira as an AI guardian angel for clinicians uh so we're kind of like a safety net for clinicians for facing medical evidence for a given situation a given patient encounter a given question that the the clinician has and so we're just surfacing the evidence we're not making any decision it remains clinical decision support um so it's really a tool to uh make it easier and faster for clinicians to surface the latest and the best much relevant medical evidence at the point of care yeah i love that quote from grandma hurts really good um or even then i have both the chance to use Mira the platform that you guys developed and i think it works really well first of all but one thing that made it stand out to me from other is there you know similar is that it takes time to really understand your query it asks follow-up questions for example it might follow up with questions about the patient's allergies or medications are on or comorbidities and that was just something that i had not seen anywhere else but i'm curious where have you actually seen Mira being into it into provider workflows is it isolated certain environments like the ER or in the inpatient awards isn't seen mostly outpatients where does it really begin to provide a workflow and are you trying to focus your efforts or do you see a one particular market or type of provider being the biggest user of Mira in the near or distant future yeah so at first it was truly a standard on application because we wanted to use it because we wanted feedback because we wanted to improve the technology and build something as robust as possible before integrating into the clinical workflow and now we're pushing towards an EHR integration with like large EHRs in the US we did the first one in Europe and that was incredible to realize that the utilization of Mira drastically increased through the EHR integration that we have in Europe which actually in a way makes sense because physicians are used to the system they're using they're used to their kind of all operation operation steps that they follow every single day and you don't want to disturb that in in any way things are moving specifically in the emergency department things are moving extremely fast it's a noisy atmosphere and things are going 100 miles per hour so asking a physician or like having a stand on application that physician should pull out to ask a question is suitable but is not suitable enough and that's how we've ended up realizing through the first EHR integration and like being able to integrate the solution like Mira seamlessly into the into the clinical workflow makes things much easier for the physician because there's no any change in no no new changes that they have to make they just have to use the tools that they're used to and they have Mira over there and that comes back to the vision we have and that sentence that that maximum stress which is the guardian angel the AR guardian angel that's every healthcare provider deserves and that's the goal and that's the vision vision for us being able to be seamlessly integrated into the into the EHR and being able to propose and provide recommendations to the physicians and the healthcare providers using the latest medical evidence and I think maybe there is a learning there for other like the entrepreneurs or people who want to be entrepreneurs but what has been the most helpful for us is is shadowing some of our advises within the ER. Because from day one, we started ourself with clinicians and we built an advisory board that we interact with on a daily basis to really make sure we are building this with and for physicians. But it's a very different thing doing this and being in the ER for an entire shift, shadowing a clinician and really understanding their work. And the difference is in the workflows between a teaching, a hospital princess and a non-teaching one. And I think one of the use cases we're really excited about right now is based off one of our observations. We like to collect patient at the glance and it's basically summarizing and digesting all the previous medical records of the patients. And that came from one of the observations with it in a very busy and chaotic ER where the physician had a patient who would not say anything about her condition and about her past conditions. And so the clinician has to go through epic care everywhere, which is this very clunky tool to have access to all previous medical history. And just go through unstructured data, tons of unstructured data to figure out how would the patient had what medications to ones on, et cetera. And so what we built is something that reads all these unstructured data and make it digestible for the clinician. That's one example that I've really a new use case we have that really incorporates in one of the workflows for users. - I don't think you've spoken closer to my heart ever in this episode. I feel like as a 30 year medical student, that's been one of the biggest things is like whenever I had a new patient, it's like you have to go through so many individual records to figure out what that patient's coming in for and what their history is. And it's so hard to find that, especially in the ED very quickly. And yeah, I can, if I had that tool on my rotations, it'd be incredible. I think physicians at some point figure out what the most efficient way is to find that information, but starting out initially, it's incredibly difficult. And it doesn't seem like it should be that difficult, but clearly you guys are building something that's really relevant. And I really think it's so meaningful that you guys are immersing yourself in the ED, like familiarizing yourself with the platforms, like Epic, you know, the outside records tool as well. So, yeah, that's really cool coming from the other side and on the clinical side. We'd love to hear more about the data quality piece in terms of the recommendations that it's pulling, you know, there are treatment guidelines that professional societies release. There are randomized control trials, meta-analyses, kind of different tiers of evidence that we use for the clinical decisions that we make. What has been your approach in teasing through that data and building that in a way to ensure that the data that's being pulled is high quality and then also, I think clinicians are particularly keen to know where their data's coming from in the sense that if they get, you know, something that is proposed, they would like to see some kind of citation or things that cite that information. So overall, just would love to hear about your process going through like the data quality piece and ensuring we have high quality clinical data for decision making. - Yeah, we're actually trying to mirror everything you just said. Maxime mentioned that in the very first days of Vera, we surrounded our system by clinical advisors because we knew that Maxime and I have the technical abilities but we're not physicians and we can't build something for physicians without physicians in the group. So we closely surrounded ourselves. We've actually people writing these guidelines with people going through that hard process of finding the best evidence to write a clinical guideline and a practice guideline. So we tried to mirror their way of thinking which actually encapsulates everything you just said. We're actually using some of ASAP's framework for that. So as you mentioned, there are a lot of class of evidence and there are actually three chairs for ASAP. So we're mirroring that. So for instance, if a paper is an RCT or a meta-analysis, it's considered as a class one of our staff of evidence as opposed to a case report, which is a class, a chair three of evidence. So that's like one of the metric that we're tracking which is the publication type. We're definitely gonna prioritize huge chords and huge statistical studies that have been made over a huge chord of patient, over one case report that has been made over one patient in a single hospital by a single provider. That's one metric. The other metric is also the journal. So each journal has an impact factor which is something we're taking into account as well as a way to weigh the evidence. Something we're waiting a bit less than the publication type, for instance. We're also taking a huge aspect of our work is also the date of publication. We just wanna make sure that we also have the latest one. So if you have two bits of evidence with the same kind of level of evidence and level of reliability, we're definitely gonna prioritize the more recent one. And there's also a whole work that we did, which is building that kind of mathematical function over all these parameters. And then evaluating our model to be able to gather the same references as the one used in the clinical guidelines to write actually the clinical guidelines. And we're using that and we're optimizing our mathematical function based on that. But it's definitely clear that it's not a trivial work. Because even if we consider the clinical guidelines, there's a lot of biases in the way that isn't chose the references. So we also need to take that into account when we're trying to optimize our own way to rank the papers. And if there was like one single mathematical function that would allow us to rank all the papers, then it would already be there. So it's definitely not the case. And it's also improving our system through the utilization by making sure that we're doing it in the most reliable way possible. But yeah, that's a combination of all of that. And of course, we're definitely prioritizing all the practice guidelines from the big journals, which is what we consider the highest level of evidence and trying always to make sure that we pull data from there. And once we have that, as we mentioned previously, there's a reasoning system that works upon that to provide answers. And we're always making sure to provide as much transparency as possible. So by citing the references, by making sure that it's easy to understand for the provider because the reference is there. We're citing directly. We're explaining how the answer is related to that piece of evidence and making sure to provide something as transparent as possible for the providers. And Tia is being a bit modest here, but he built during what actually a proprietary benchmark that we use internally called guidelines QA, which evaluates the ability of parameters to mirror the guidelines of the process of writing a guideline. Because we have our huge database of primary literature. And then the guidelines are because they're secondary literature the same way it looks data is, right? And so what if our reasoning models, because they can reason well enough and understand the frameworks that are used to write A-Set guidelines, for instance, we're able to write guidelines only based on the primary nutrition. And so that's what we're trying to evaluate now. And that Tia has built an entire data benchmark that we evaluate the remote against, again, again, and again. But for now, we're still using as primary source the practice guidelines. - Yeah, I mean, it's nearly impossible for the organizations that write the guidelines that providers use in their day-to-day practice up to date, because new literature, new research comes up pretty much every single day. And you only update it so often, whether it's every month, six months, every year, however long, whatever the intervals are. So it's really fascinating the idea of an AI being able to write its own guidelines based on the most recent research or results that you can find. Whilst still keeping in mind that research may or may not be reliable and may or may not be accurate, and that you need a lot of factors to come into play before actually modifying guidelines or modifying how providers are pre-interpatiants. But shifting gears a little bit to your go-to-market, you mentioned that you first started trying to find pilots or customers back in last July. So I'm curious, how did you approach it? How would you go about finding your first pilot and getting someone to trust you enough to give you a shot? Because after all, you were essentially a known-name company that had never sold a product before. You didn't exist a year prior. So how would you navigate that? Was it reaching out to contacts you already had? Was it reaching out to old mentors? People you've already knew? Was it a cold outreach? How would you go about finding the right people? And then once you found them, how would you convince them to give Vera a shot and do a pilot with you? I mean, it's a tough field. Healthcare is. is extremely tough. And we first, as Maxim said, created that advisory boards and surrounded ourselves with physicians and actually creating deep connection with each and every one of them to truly understand how they do things, how this tool can benefit for them first before going anywhere else. And yeah, so we've been, we got a lot of introductions from them directly, from some of their friends, from industry leaders, from people who can actually try out our product and give us feedback. And during WIC, it was kind of funny because maybe two weeks in, we ended up having like, maybe a hundred WhatsApp groups, with like a hundred users just to gather feedback and continue gathering as many feedback as possible to improve the technology. And I think it's truly there. And one of WIC's advice is build something that a few people love. And that's exactly what we've been trying to do on the early days to make sure that we build something that is as tailored as possible for our very first customers. And then for the Goach market, it always comes back to having champions within hospitals. And once you actually have one physician that used your product for a while, that actually loved it, that saw some satisfaction, that showed how him, it made his whole life easier in a way, then he can champion it within a hospital. And that's basically the approach we've been taking with Vera since the early days. Our first pilot was exactly that. It's a chief emergency physician who has been using Vera for one month. He didn't believe us at first. He did like one or first two questions. He was using another tool for a while. He loved it. He continued using it for a while before introducing it to all the residents and all the other attendings to the hospitals. So it's truly there. In a field as sensitive as healthcare, you can't just sell something to a whole organization to a whole hospital, because the consequences could be dramatic. But if you actually build something slowly enough, but in the most reliable way, and have some early adopters that truly love it, that don't see any flows, or at least, if you're able to show that you're able to turn out these flows as fast as possible, then you might have your way in. And that's basically what we've been doing so far, building trustworthy relationship with physician who are users, who are helping us every day toward our goal, and who are mentoring and championing Vera within their own institution. Yeah, and just to follow up on that, I think we really appreciate the thorough response. And it sounds incredibly daunting. I feel like especially knowing how the hospitals operate on the clinical side of knowing how difficult it is to make any kind of changes, to have you guys make such an incredible product within have to face the friction of integrating it into a health system. So I'm sure that's difficult, and it sounds like you've been really diligent with that. Just one question with the way that you approach selling as well. In healthcare, particularly, I can imagine it can be really hard to sell directly to health care systems. And I'm curious if you ever considered going directly to individual physicians. The example that I have is, you know, when I think one of the first waves of the generative AI tools that we're being built was in the clinical documentation with like ambient note generation. And there are a few companies in the space, but one of them was called Get Freed. And that one was unique because you would see Instagram ads for it. And like anyone could just download it and use it individually. And it was a bit more compliant. Meanwhile, there were other tools like a bridge and no text, which I think were more B2B focused. And I mean, there were two completely different marketing strategies. And I'm sure they command different users. I'm just curious if you guys ever thought about going directly to the physicians, offering it to individual people. If they wanted to, whether that's on a one-to-one basis or even smaller clinics versus larger healthcare organizations that would be more B2B model. That's completely on points. I mean, that has been a non-going discussion between the 12th and the 12th for a while. And actually, we're in discussions with Frid with Errors there. So we know them. And we really like their approach to going bottom up instead of top down, which for sure makes a lot of sense. The main issue with this being integrating within the workflow and within the HR. How can we-- for our tool, which is Niko the Srin support, integrate within the workflow of the clinician? If we don't have the clearance from the healthcare system. Then the first one and the second one is one of her value propositions is integrating the healthcare systems internal guidelines and protocols within our knowledge base. But that whenever they have a query or a patient, Vera understands the context around the encounter. They're in these healthcare systems so they have this specific pathway for this workup. And so we're going to provide this. So for these two reasons, we have focused on top down approach. That said, now we are CME accredited. So it's also a value proposition that we can provide to individual clinicians saying, hey, we're provided with free semi credits. So that has been an ongoing discussion with Tayapura Y. And we're not closing any doors. It's actually funny that you're asking this question because we're discussing it no later than yesterday. But we've also found recently like an in between, which is integrating with smaller EHRs, which is the first thing that we did back in Europe. And we integrated with that EHR that provides solutions to individual practices. So we did that and it turns out like being a great in between because that still kind of mirrors our own will to be simultaneously integrated within the clinical workflow. As Maxim said, and yeah, but that's, that there's actually a very interesting video that we've been introduced to by one of the partners of ACXXNZ, which is the kind of the B2C2B approach. And it's definitely something we're considering being able to have early adopters and a lot of early adopters within the same institution could be a good way to go, a bottom up. But once again, the EHR integration is a huge barrier. And I think we surely believe that will offer the most through the integration. - That totally makes sense. I mean, if you are able to get enough grassroots support, you can have sort of a bottom-up approach where there's enough providers, enough physicians in a hospital using it, that administration sort of has to implement it and work with getting integrated into the hospital because that's what their staff is calling for. But at the same time, it's sometimes a lot harder to get an entire system to agree to give you a shot compared to an individual provider, individual physician because it's lower stakes for them. They can just give it a shot, it doesn't work. Stop using it. But a minute ago, you also mentioned that you are working with systems in both the US and also in Europe. That's really intriguing to me because I'm curious, how are you navigating that? Obviously the health systems in America versus in Europe are very different. America has a lot more privatized, the deal with insurance, you have to deal with all these different things. But even the day-to-day workflows are very different of providers in America versus Europe. In addition to all of that, European data security laws, GDPR requirements also just add a whole other barrier. So if you don't want to share, how are you differentiating your approach in Europe versus here? And what different strategies have you had to take because the differences in barriers or differences in the systems you're navigating? Yeah, very interesting. And there's also something else that you didn't mention, which is purely from a type of perspective as well. Like if we're in Europe or other countries we'll have to prioritize other type of guideline rather than just American guidelines. So it's also something that was in our mind that we had to take into account. In terms of security, we handled everything kind of a similar way as we did with the heap of complaint to be GDPR. And then when it comes to the integration, we were lucky enough because the ESRO that we integrated with has been founded by tech, savvy people who decided to do everything by themselves. So we actually have an API in points. We made like a very detailed documentation of how our API could be used. And they integrated directly into what makes the most sense for their physicians. We also talked to some of the physicians to actually understand more about certain news cases, such as the patient at a glance one, which is the first input that we created. And then push things forward. words. But yeah, the great thing is the EHA is actually also responsible of the distribution. So we keep focusing on the US while tapping into another market where the EHR provider has actually serves a lot of different individual practices. It knows how things worry because he's been there for, they've been there for a while now and they were in charge of doing the integration themselves in their software in the way that makes the most sense. Yeah, it's really incredible to hear just the amount of variability that you can have with these tools and you know whether that's even within the country but then also internationally. I think one thing that has is going to be really interesting is at least historically the go-to clinical resource before I think the AI boom was up to date like everyone that was in a hospital like Reese uses up to it and still does but I think the AI clinical decision support tools are really making a dent now and almost replacing a lot of the work, a lot of the things people are looking up and people are just plugging it into their go-to CDS tools. And I think that's interesting because while up to date was the premier evidence source before now coming into these into this time, it seems like there's multiple clinical decision support tools that are being built kind of concurrently with different emphasis, emphasis, I guess you have open evidence, you have AVO, Glass, Vera with you guys and it just sounds like there's such a competitive landscape in this clinical decision support space right now. We'd love to hear more about how you guys are navigating that. What you guys think sets Vera apart from the competition and how you're approaching it from a unique lens. I think we're really excited about this competitive landscape. First because everyone has taken a different approach and it's exciting to see which approach works better in which situation. We think open evidence is an amazing tool, they have a great technology and amazing team and the fact that it's open access and anyone can use it to ask a simple question is remarkable. And we've discussed with a bunch of residents, the most residents we know actually have used in these ones. And then there is AVO which is also great. I think they were one of the first ones really trying to focus on the guidelines with this opinion, it shows, hey guidelines are the best, let's not even look at the primary literature and let's try to from day one and I think Gary mentioned it on your podcast, Integrating to Epic which was a bold choice which we're making as well now. Where we are differentiating is really on this integration within the workflows. So it's less about the core technology even though we have differences that AVO will probably want to mention but also on the integration side of things. Where in the workflow do we integrate and what aspects of the burden, administrative burden mostly or documentation burden do we alleviate. And so for us it's been navigating the technical pathways for instance, getting access to the internal protocols and guidelines of the hostels that we're mentioned. And so these are things, these other tools are not doing at least yet and that we really think make a difference for the clinicians. But I think it's very exciting to see different actors going in a slightly different directions and seeing how we're going to all come together at some point. Yeah, that's a really good point. And I mean, I think that every CDS system whether it's Vera or Glass or AVO, they all are approaching the problem in a slightly different way. They all have their own unique value propositions are trying to put their own twist on it. And it's going to be very interesting to see which one actually may share in different areas. For example, is one getting more popular in patient, while others are more outpatient is one getting more popular for emergency medicine or internal medicine or cardiology for example. And it's going to be interesting to see how the different companies, how you all learn from each other and how you all adapt to be the most competitive and to be the one that gains a majority of market share. I mean, the only thing we know for sure is that CDS is going to play a pretty big role in clinical decision making in clinical practice from here on out because it's already sort of revamped how providers go about their day about how they make tough decisions or how they do research even. So that's the only guarantee but other than that, we just don't know what's going to happen. But shifting gears just a little bit, you've obviously come so far since last summer since you joined YC. Since then, what has been the biggest challenge or obstacle you've faced? What's been the biggest hurdle that you've had to overcome to get to where you are now? And how did you approach it? How did you address it in order to be successful and in order to gain the traction you have so far? I think the biggest challenge, which is also, which also ended up being the biggest mistake we made, was not going to the EG sooner. We talked to so many physicians and we actually learned a lot by learning from their own experiences. But going there and actually seeing the realities completely different than what you thought and what you heard. So the biggest challenge at first, while being at YC and having to work on the tech, on the product and the engaging so many customers, just covering calls and understanding better the use case of each and every of our users. We didn't have the chance to actually go there and shut off physicians and it took us a few months to actually have our first EG shadowing. We had the first one and we decided to multiply it as much as possible to truly understand how things work internally within EG. And that's how we ended up coming up with more use cases that are way more relevant than what we would have believed before. That's also how we ended up coming into the conclusion that the EG integration is a must at a point for us. We also saw a lot of nurses and other providers looking at some pathways and decision trees stuck on some walls. And we also saw huge books hidden somewhere in the closed-ed in the EG that no one uses. And when we asked about this book, we realized that it was all the procedures that healthcare providers have to use. And we came up to the realization that maybe the biggest use case is also being able to integrate all of that into our search engine and provide a tailored solution. That also comes back to the question you were asking before about our competitors. We truly have a specific compared to open evidence today. I don't know where open evidence is heading towards, but today, the true differentiator for us is to provide something as tailored as possible to the healthcare institution. That goes even beyond the simple, I mean, it's definitely not simple, but that goes even beyond the EG integration. It's providing a tailored search engine for them, because each institution has specific guidelines that they can follow and that they will follow. That's sometimes if you differentiate from the national guidelines, then there are a lot of reasons for them. Sometimes just operational reasons. If you have to do an MRI for this and this kind of patients, but it turns out that you only have one MRI or you MRI doesn't worry during the weekend, or you have other issues, then you need tailored decision-tries and tailored algorithms for your institution. So for us, it's truly about finding that and providing this solution and that was the biggest challenge for us at first. It was to truly understand the needs and I think there's no better way to understand the needs than being there, because sometimes physicians will tell you stuff and they would not even come up to the realization that this was, this is actually the biggest mistake they're facing, the biggest need they're facing every single day, but when you shadow them and you ask them about that, that need and that issue that they're facing every day, it comes up as a realization. So it's truly being there and being able to understand more closely the biggest needs that the providers face on a daily basis. And maybe to add on that, even though it's going to be a very long answer now, but one of the main challenges we face, maybe as a health tech startup, was to try and match the velocity of a YC startup with the slowness of the health care administration and health care systems. And so we've had to navigate the stakeholder discussions between like in a large health care system, who should we talk to, who should be our champion, and this has been a big challenge for us, and I think for every health tech company that we know of, one of the other things that we've had realized was, okay, maybe elevating the standard of care is not the top priority for health care systems. And so how can we frame our value proposition, so it's not only, which is weird to say, but elevating instead of care, also providing an ROI for the health care system, so that not only the medical champion is interested in getting our solution, but also the rest of the stakeholders. That has been an actual challenge, I think, must have the companies we know face, but it's an dressing journey. It's a very interesting journey, but I would say you have to passionate about health care to stay in that journey. Yeah, I can imagine you guys clearly are super passionate if you're able to stand the test of all the things in your way to get through it. We'll have to hear a little bit more about the future of Vera at least in the next few months. I know it's start-ups and moves so fast. It's hard to say like in a year or two, but what are you guys really excited about what you're working on right now and what are the next few months into this into 2025 look it look like? Yeah, I mean it's truly about keeping the discussions as close as possible with everyone surrounding us, being able to go more often to the EG, understand better the needs and provide the solution that is tailored the most to the needs that health care providers have. We came up with new very interesting use cases that we're going to share pretty quickly, but yeah, it's pushing the boundaries of what is doable, being that AI guard an angel for every physician and being able to provide a solution and in from a business perspective for Vera that that would actually mirror what any stakeholder would want because the CMO wouldn't necessarily want the same thing as the CFO and it's yeah navigating that complex landscape and keeping the ground on the earth by the feet on the ground by providing the most the most efficient and most reliable technology and and pushing pushing the boundaries every single day. And maybe on the pragmatic side of things we're going to spend the next couple of mountains in Francisco, surrounded by mostly white sea companies, getting our first couple of hires on the engineering side and on the clinical side. So that's very exciting as found as to bring people on board with us that really believe in their mission and from a technological perspective like the next couple of months are I think very exciting for every AI company because for us every improvement that is made in like there had been so much in the past few weeks is truly transformative for our technology. So I think the next few months are going to be very exciting for us. That's amazing. I mean yeah it's so hard to keep track of everything that's going on in the AI world these days. New models constantly being developed, new agents. I've seen AI agents using other AI agents to code or develop software or just do complex tasks. It's fascinating and it's going to be really interesting to see how the industry evolves and how companies like you guys have Vera and other companies in healthcare space make use of all these new developments and really try to provide the most value for providers but also other segments whether it's patients or health systems as a whole. Now we've asked a lot of tough questions during this episode and I think you've done a great job giving us a ton of insights but let's let's we wrap up let's ask a little bit of easier question. A lot of our listeners are people who are interested in healthcare innovation in potentially starting their own companies or developing their own platform for solutions. What advice would you have for an aspiring healthcare AI or healthcare entrepreneur in general? What tips would you give them or what would you tell them to inspire them as they potentially start their journey? It's not the easiest of questions. I think for me I would say two things. The first is surround yourself with people you really want to work with. So I think it's a blessing to be able to work with a friend and that's like the main thing as an entrepreneur is you're going to go through hardships and loads and highs, a lot of loads and so you want to be surrounded with people that you want to share this journey with. That's the first one and very especially to healthcare if you don't have to integrate with Epic please don't and just stay away from this. Yeah and on Mayan it would be it's it would be similar to any other industries but specifically for healthcare essentially green and resilience. Don't stop, keep moving things are moving slower as I started which is basically the biggest killer for started but keep pushing and resilience is probably the biggest thing you need as an entrepreneur and specifically as a healthcare founder or entrepreneur. It's been incredible having you guys on. I feel we've learned so much and you guys have been very open to sharing your struggles and also your growth and just your journey building and spend an incredible experience. Thank you guys so much for your time. It's been an honor.