BoneChat #123 - Amazing AI Tools for Startups: Finding Early Adopters, Top Sales Talent, and Funding

This is Bone Chat 123. We've got Stephen Flutie Davis with Encircle, and he's got some new tools that startups need. Um, we're today we're going to talk mostly about how to vet early surgeon adopters. Um, and you know, there's a lot of mistakes that companies make. Um, they go out and get the big name and not the best early adopter. They, or they get somebody that's just an echo chamber, uh, just tells you what you want to hear, or they get a tinkerer, somebody that wants to change things constantly. There's just so many things you can do wrong. So he's got a way to vet this. So I'm gonna hand the mic over to Steven.

Thank you, Tiger, appreciate it. And I'll go ahead and share my screen so we've got some slides for it. All right, so, so EnCircle itself, AI-powered commercialization growth engine, helping companies solve, there we go, helping companies solve, I think, some of the biggest problems around device development and commercialization, which is where do I launch? Who are the doctors that are gonna adopt the product first? Finding proper KOLs, building out even before launch, a good design team. How do we identify those physicians? From there, it's who's gonna sell the product? How do we find distributors? How do we find regular reps? And then the next one is if you go to W-2 reps is how do we know that this is the right rep if someone is not working with someone like you, Tiger, on the recruiting side? And so it's just a 3-tiered platform that we've seen firsthand of some of the biggest problems to be able to develop a company. So many founders or companies think, you know, the hard part is the FDA. But realistically, there is a clear-cut path. If you do this and you do this and your studies come back as Y and you are, you know, in a good spot, then you should be able to get a $510K. So there's a pathway for that. For commercialization, it's where you see so much money just burnt and just wasted of trying to find the right physicians to take on the product, trying to find the right reps to sell the product. And that's really what we're trying to focus on, on doing is streamlining that process. And early adopters is an interesting topic that you've talked about, that a lot of us have talked about, is how do you identify them and who are they? And move the slide over. And for— by now, the industry is kind of looking at how do you target physicians based off of a volume-based approach. And for us, volume-based is really a year's— looking at data from a year from behind. And there's a lot of discrepancies in these these datasets. And unfortunately, it's not because of the acuities of the MedScouts or the Definitives of the world. It's just no two surgeons typically bill the exact same way. So you tend to have some frustrations there. Or if you're trying to find a new physician, one of those fellows coming into practice, there's no data behind them at all of what their essentially CPT code usage is. We went about this a different way. How do you socially profile, financially profile physicians? Who are they? What are they interested in? And would they potentially have a conversation with me? So we built a dynamic scoring algorithm. The core of it is based off of Rogers Diffusion Theory. I'm not sure if either of you two have read the Crossing the Chasm book. No. No. How do you identify the first 16% of the industry, the innovators and the early adopters and the science behind that? And so we started to identify the 16 behavioral traits of who these, you know, who these early adopters are in the technology space. From there, we looked and built out— we found 50 studies that looked over 6,000 physicians and the innovation techniques and concepts. Who are they? What are they interested in over the past 50 to 60 years? And started building out our own algorithm on that and then our own database from there as well. One of the other big things we wanted to focus on is making sure it was very easy to use. We didn't want someone to look— open up a Salesforce-looking tool. While they're extremely powerful, they're also very overwhelming, and there's almost— you don't know where to go on some of those. So what, what's working well, these ChatGPT-like interfaces. That's, and that's what we wanted to do, make it very user-friendly and very easy to comprehend the data and make that data truly actionable. And so that's product number 1 here. That's, that's our, our in-circle GTM, our physician early adopter product. And we'll go a little bit further into it from here. Again, no more CPT code data. All of this is really based off of patent information. You know, you can figure out who these physicians are, if they're involved in any type of development conversations or they're getting any royalty type payments. And you could actually see that live. You could search by publications, conference presentations. You could even look for physicians that are in a specific fellowship program. So if you're getting ready to build or launch a, let's go say, a meniscal root pad product, or if you're in the ACL space, you can actually search not by who's busy in that space, But who's actually active in that space? And we can search by, find me doctors that have patents with ACL implants or loop tech, whatever that might be. And you can identify them in real time, see the patents and who those patents have been assigned to and if they're open or not. And the reason we look at that is to us, that goes layers deeper of, okay, this person's busy. That is, oh, this person is willing to take the next step to actually push through something that they've wanted to do throughout their career. So to me, that means that they're an early adopter of some capacity. And when you see in here, our database will actually have essentially a slider scale of early adoption, and it's all based off of what you're asking. It's a very dynamic program. And please stop at any time if you guys have questions on that. And the demos are more fun to go through than the slides, so we'll do that. So that's kind of, you know, how to find your early adopter physicians. Who are they? All that fun stuff and search in real language. Then it's who's going to sell our product and why. And that's where we built out a tool called RepGPT, which is essentially a medical device distributor sourcing platform. This parses through over 800 million LinkedIn profiles, Facebook, GitHub. There's, there's over 50 data points that we've moved through here. Now we've got 5 layers of AI parsing and ranking tools to be able to actually identify who these individuals are. Say, find me, find me orthopedic sales reps at Stryker or Zimmer Great Lakes in Chicago or Dallas, and it'll find them, rank them, and you see their LinkedIn information live and get their contact enrichment right then and there. So if you're scaling, trying to find distributors, there's no better way to do so or easier way to do so. Version 1 searches right now where we are directly into their job post— sorry, their, their job titles. The hard part is you've got agency owner here, principal distributor here, all that fun stuff. So we're building it up to make that a little bit more reproducible. By the end of the weekend, you'll actually be able to search not just by their job title, but what's the title that they put on their actual LinkedIn, and then what their about section says. And that now will become searchable by the end of this weekend, which should greatly enhance our capabilities of that. On the other side, we do have essentially two-sided network as well, where we do have a network of distributors that are looking for products that they want to pick up, and we'll show you what that looks like. This is free for them to use. It's like medreps.com. But it's not paywall. And I think that's where the mess is up there where I, I was a distributor, I was a rep. You'd sign on wanting to find a new product, you paid even if it was $20 and you wouldn't find anything in your area and you just got burnt from that and you just felt like you didn't want to be part of that anymore. So it's very important that we built something for the distributor side of things. And so between RepGPT and, and Encircle Connect, I think there's, there's no true better way at this point to be able to identify distributors and for distributors to be able to say, okay, well I know that product. Oh, they're also hiring in my area. Now, 3 clicks of a button and an email sent directly to that hiring manager. It's pretty fun for distributors on that side. And we've got a few hundred that have joined to date. They've been, it's been pretty beneficial for the companies we're working with. Now comes the question, who are the right reps that are gonna sell this product? So we, I worked at Stryker for years. I've done a ton of those Gallup polls. Love 'em or hate 'em, they're efficient. They, they work pretty well. You know, people that do well on that poll typically sell better pro— you know, they do better in, in their sales. And so what we wanted to do was build that concept into an AI interviewer that was cost-effective and scalable, mainly for medical device distributors to be able to have access to those same tools. Tiger, as you're aware, it is very expensive to make the wrong hire. And so what we wanted to do was make something very easy, very cost-effective for not only distributors,, but recruiters can use it, startups can use it just to be able to kind of say, okay, or even these major companies, the Strykers, the Smith Nephews of the world can use. So in a very cost-effective and scalable platform that gives you actionable data of who these candidates are, where are they strong, what do they need work on, and then give you follow-up questions from there. It's as simple as you just put your job posting URL or description into the field and it'll build its own questions for you. And a dynamic scoring algorithm based off of location, seniority, but it's all focused on medical device. It's a really fun tool and we'll, we'll demo that here live. And then that's kind of it right now though. The way that our model works is essentially it's a subscription model. The RepGPT has a little bit of a change where it is, it's subscription, but there are limitations to how many contact enrichments you can actually get per month, but you could top that up at any time. Lower subscription to the platform, pay for more usage when you need to. So therefore we can bring the cost down rather than spending $25,000 plus $2,000 per user. Ours are significantly cheaper. And it's fun the way the model kind of works now is you get companies hooked with the biggest problem I think out there is who are the early adopters? Who am I going to build my KOL panel with? I have an idea, but who's going to build it with me? How do I find these doctors? So you get them looped in early here, which funnels into now we've figured out who our launch team is, who our development surgeons are. Who's going to sell the product. And that's where RepGPT comes in. RepGPT has email capabilities, so companies are emailing from our platform and going right to Connect, and then the distributor database just builds with more users we have. So really building a flywheel of user growth, which is different from what we started of us just manually doing recruiting for distributors, which is, as Tiger, you're probably well aware, very challenging to, to do. So now we open up the tools just to be able to give companies access to have more of like a sales enablement platform All right, we can go directly into a demo. So anyone on the team looking for early adopter surgeons of anything that we could search for?

Well, let's, let's, let me ask the question. Share a story of a KOL that didn't work out.

Because, oh man. Yeah. His names, real names, obviously, but Yeah, I mean, most of the product launch and development that I did was at Stryker. So you kind of had your teams built in, but man, you'd have some that were just so— I wish I had this when I was there, essentially. And I'm doing some consulting for another company now that, you know, is coming to market in the next few years. One of the biggest things they wanted to try to identify was how do I find KOLs that are a part of a specific study? And how do we profile who these physicians are? What conferences do they attend the most? And then from there, you kind of build your own kind of dynamic marketing program based off of, well, these doctors that I want to engage with to find a good KOL are most likely at OSET. This other group is most likely at the ACIS conferences, or they foot and ankle, or this and that. So, you know, that's one part. I do think when you're doing sales training and you're a rep, It's always now volume-based. Go after the biggest target out there. And when you look at that, it's— I mean, it never really works when you go after the whales of the industry. I mean, I sold for years. I taught these sales training courses.

Yeah, that's a big mistake. Hey, Kyle or John, what's— give me a bad KOL choice. Give me a story.

Uh, what if they eventually get sent to prison and lost their license.

That's an extreme one.

Yeah, that beat mine. Uh, I certainly know and have experience where there's a, a very big name, everybody's very excited, kind of an expert in that space, uh, and then through the process of early use, uh, never really uses it, always finds a little problem like why we don't this, or it never pushes it through to get approved on hospital on the hospital that he or she works in. Um, and I certainly know of, um, and maybe eventually they come on, but kind of that early, you know, a lot of effort and hype, uh, around a specific kind of niche, uh, and they, and they just never, you know, they're willing to participate in the meetings and participate in the design talk, but they never execute, I guess. Uh, so not give me names, things. I mean, I don't know if that's, uh, if people have experienced that, but I've seen that a lot, John.

That's an early adopter when it comes to royalties, but they're a delayed adopter when it comes to technologies.

Yes, I think that's a great way to explain it. Yes, 100%.

You know, we've tried to identify how to fix that problem. And so we pull in live pull from Sunshine Next. So the CMS Open Payments data, but we essentially look at if a physician is getting paid by too many companies at this point, is there a deduction in their early adoption of a technology? And the answer for us is Yes, because you want to be able to see like, okay, well, this person's doing this, this, this, this, this. How are they going to be able to properly give you the attention that you need to, especially like you said, when it comes to the VAC program? It's really hard to be able to do that.

I've got— I may have one here, uh, Tiger, that I was just thinking about this. So a company that I was a founder in, and it's out and running and doing, doing well, but I know that likely their market is tough. So the Endeavor Orthopedics patella plate, right? So it's a patella plate Every surgeon on the planet uses, you know, one a month, right? Like, oh, the general guy, the trauma guy, this. And so they are hard to find. And so I, again, I don't know exactly what they're doing because I'm not managing the company anymore, but my guess is they're probably trying to figure out like what CP— like who's putting in the most CPT codes for that. Yeah, but I, I know that's been a challenge. It was a challenge for me, and I know it's probably a challenge for them. It's like, where are all those people? And then I'll throw in a business pitch is once we identify them Have you guys heard of Overland Mobile Labs? They should go do a lab with all these guys. I'm just kidding.

Go ahead.

I'm kidding.

Go ahead. Yeah, that's funny.

Steven's done a search and he's found a bunch of patella fracture injures.

I mean, that's so— I mean, I don't know if anyone like Greg Peratto is on this call or Ryan Stafford. They may be, but this might be very helpful to them.

Yeah.

So I don't know, you know, again, this, this now goes through, we've got 9,000 physicians in our database. It's not about finding the entire industry. It's about finding the right part of the industry that's going to actually help you get to the tipping point of adoption and for a company like yours, that early revenue generation. So that's, that's the key focus of why we built this. We don't look at CMS data. We do look at over 150 data points for physicians, including of academic affiliation, and we do not count that towards early adoption because of the VAC programs and getting products in is actually more challenging there. So where most legacy data out there, not data, but the studies have said, well, if they are part of, at least it's not true in orthopedics, if they're part of an academic institution, they're an early adopter. Well, that may be true, but the facility doesn't allow that to happen.

You get it in the door.

Exactly, exactly. So what we do is we look at the patent history, we look at their conference presentation, their podiums, their podcasts, Their YouTubes will be searchable very soon. Um, their, their PubMed kind of— there's over 150 data points. It looks very simple on the front end, but the back end is kind of the craziness and the chaos. So we'll go look at Dr. Brandon Yon here. He developed novel fixation constructs, Wagon Wheel and Omega Plates, for patella fractures. Publishes extensively on trauma classification, blah, blah, blah. Uh, collaborates with Stryker and Synthes. So you know ahead of time. The score here is what you'll see is if you are in our database, you have hit our threshold of you are an early adopter. So you have a base score of 40 based off of what you ask. It will show you how likelihood of they are that specific question that you're asking of it. So it's not if they're an early adopter, it's the early adopter of what capacity to what you want to try to get in front of these people for. And that's what we were really focused on. So I'll pull, click on his profile. This is a live pull from LinkedIn now, so you can actually pull in their LinkedIn information. Why we also did that It is nearly impossible to try to find physicians' investments. It's— we have another investment platform that Tiger and I have talked about and we'll present on that another time. But we've gone through SEC filings, all that. It's impossible. But where they do post it, their LinkedIn. And that's why it's very important because that is becoming searchable for us now. So, you know, find me physicians that are advisors at X, Y company. It can search for that information. This is a live pull from their publications., and you could click directly on their publications from here and see anything that they're doing. You can look in their clinical trials, what the status of the trial is, go to the clinical trial, their patents— he doesn't have any— conference presentation, we don't have any for him on here. Um, we are significantly building out our OTA database right now and some of the other smaller. So we've got about 29 conferences. Trauma is where we actually have agents that are building out all that data, and that should be I think we should have 4,500 new trauma data points this week. So, um, live pull in their financials so you know who they're working with. Um, and we'll go back, we can look at, you know, a couple other doctors somewhere else. I want to find someone with patents for you.

Uh, and is it— um, and Stephen, sorry to interrupt, is it— uh, it sounds like— so you guys, again, I'm turning into my dad as I get older, but I'm assuming you guys have basically built an algorithm that searches using AI, searches all of this information that you guys have said, hey, this will be important to make these decisions. And then you've kind of directed it to here's how we rank them and here's why. So you've got a proprietary software or search engine that's, that's using AI to get this. Is that, is that— is that— sorry about that.

Yeah, no, that's accurate. Essentially what we've done is build our own database. So from— we've started this past summer, like, went and built a database of essentially what we think is the most important part of physicians. Who are these physicians that are presenting? But more than that, who are developing all, all the, like, the 150 data points per doctor. And then from there, we continuously are partnering and building out our data sets with— we have all the top-tier programs. Now it's the OTAs. Now it's the regional trauma conferences, the regional foot and ankle conferences. And all those abstracts, all those posters, their podcasts, those presentations become actionable data here. The open mic nights with Joey, where that was seen one time is now searchable and actionable for the industry to be able to say, well, that's great. I didn't know that conversation happened then, blah, blah, blah. You know, so that's, that's how we looked at it. For reps, it's nice because you could look up a doctor's name at the board and it'll do that live pull right then and there. It won't rank them as an early adopter, but you could look up that information live and takes about 30 seconds to do so.

Okay, very cool.

Thank you. You're welcome. So the difference between also that there's, there's there's a subscription for reps, there's a subscription for the executive teams and the marketing teams. Kind of the bigger thing that we're focusing on is reps don't care about patents, so they're not going to see patents, but the marketing teams in the very near future— and John and Kyle, love your feedback— if this is a pain point, you found this person, now how do you contact them? And that's, I think, one of the problems that we want to go down. Is that a pain point that you both have had?

Yeah. Oh, yeah.

Yeah.

Okay.

Yeah.

Yeah.

I have to kind of search my network. Does anyone know this person, right?

Is—

well, it's gonna be a one-step click. Here's their phone number. Here's their email and try to make life much easier for everyone, especially when you're pre-commercial trying to figure out who's gonna help me design this thing, who's gonna build my, you know, my, my surgical technique. So, so that's kind of how it looks from here. I wanna find another one. Surgeons or with patents— whoops, be good if I could type— in ACL implants. The fun part is you just can, you can search the patent, you can see if there's out there, you can look at it live, and then who that patent has been assigned to.

What's the LLM in the background, Stephen, that you're using there?

There's, uh, different levels of Claude, there's different levels of Perplexity, there's different levels of Gemini. So we're using multiple. We've completely eliminated OpenAI from here. Claude is doing a lot of the reasoning, but each actual pull is a direct API call from our database as well. So we've got a guy that's brilliant, the second master's at MIT, that has helped us put this together. And at this point, since, you know, this craziness in the AI world in the past just 6 weeks and 6 months, our team has not really been sleeping, trying just to stay on the cutting edge of continuously installing and fixing new tools that also drives everyone's cost down. So here's someone we just looked again, you know, patents within the ACL space. Could be an interesting way for you guys to look at, you know, how do we build out our launch team or our new targets for, you know, for telefracture plates to see anyone that has any type of patents on plates in that area. But you can click on this and click on the patent right here and see, okay, who— what is the patent one? So it's femoral guide, and then who the patent was assigned to. And that's nice because now you can go layers deeper to know they're most likely working with Smith and nephew. It might not be a good launch target for you, or what's going on with that product? Was that product discontinued? Maybe that is a good launch target for you because they're upset. So that's, that's how we built this platform out. And then we have a comparison tool as well where you can look at— we're doing, you know, knee doctors in Chicago. So I'll just go ahead and look at these two doctors here. And now you could do a side-by-side comparison of who they are, what, who they're involved, you know, who they're getting paid by, any speaking presentations, their clinical trials that they have going on. You could also take it a step further and generate a full in-depth intelligence report. This is more of how do you build a dynamic marketing program for these types of physicians. We were looking earlier of all the doctors that are on BioBrace, and so we found, um, we narrowed it down to about 15 that we wanted to target for this client we're working with. And then from here, built out this report of these physicians on this side attend this conference the most, and these others on this side, these ones are presenting here or focused on these topics. It takes a minute because it's, it's a pretty in-depth report, but every single claim that is made of this physician is interested in XYZ also has the reason for, uh, of Rogers Diffusion Theory underneath it as well. So again, takes a few seconds, but it's well worth the, uh, the wait. There you go.

Do you have— do you feed the database with, uh, the disclosures that surgeons give when they go to conferences? Like, you know, I'm being paid.

We just looked that up live. Um, what we want to do very soon— we've been quietly building this, we haven't really put too much effort, you know. We went and announced at Academy, we got the booth, we did the co-sponsor with Joey Ship.

It was great.

We, we had a a bunch of companies have signed up. But from there, we kind of wanted to refine the model a little bit. What we also want to do is use the Crunchbase method. Crunchbase went and peeled out all these public— you took all the public information of investors, said, come claim your profile. We're starting to work with physicians to do the same. What are we missing that's not publicly available? And what are you interested in? And so physicians are starting to come claim their profiles now. So you can actually see, you know, I'll go back to it, but you'll see physician enrichments of everything they put in there as well. But this is nice because you can essentially see, you know, what they're interested in. What is this person actually interested in right now? Using biologic treatments. How central is it to what their, their focus is? It's pretty central. This is an emerging topic for them. And then again, Roger's significance. This research topic highlights innovation characteristics through investigation. So it's really baked into the data of and the science behind who early adopters are. And then you could export that to a report. So John, Kyle, questions on this one before we move over to the, how do you find distributors to sell this?

Nope. I have, I'd like to see you do a search on building a KOL team like you suggested before. We can come back to that later.

Yeah.

Yeah. Yeah. And Steve, can I ask just one question again? You know, I use AI quite a bit on, you know, Claude and some other things. How, and again, I know I'm asking a biased question, you know, I know you're a little biased here, but how accurate do you feel that the information that comes out of here is, or are we, is it kind of subject to regular AI issues like, hey, you might want to double-check this or double-check that?

What? I mean, there's always going to be AI hallucinations no matter what systems you use or how good you are being able to, you know, like you do a Grok search and you're like, Grok, that's not accurate at all. We've done pretty good of being able to say this is the data. All we need to do is analyze the data based off of this scientific data that we built in here. So we do have a pretty good reliable algorithm in place. So the guys that are building it are MIT AI engineers, much smarter than I am, and they, and they've been able to make this more reproducible. The questions here would be where you would get more hallucinations rather than very, not very common that it would, because it's just doing a, this is the topic that this person looks at. So this is essentially the research that backs this type of usage. When you look at the finders, this is technically public information, so there's no true hallucinations from here. This is, we built a sequence algorithm. Is this the right doctor? Does it match their MPI? From there, their MPI taxonomies are also not always accurate, so that's sometimes frustrating. Now you go to about 10 different websites, Zocdoc, Telehealth, Healthgrades. Is this the right person? Is this the right location? The location was probably where we were getting the biggest hallucination at first. Then it says, yes, this is the right, the most accurate information. Now we go and pull the rest of the information from there. So it's now essentially a unique identifier finding that person throughout the internet. From there, we then put through a quality, essentially enrichment, essentially algorithm that we built as well and workflow. So if it matches a certain threshold, then it's allowed in. If it doesn't, we don't allow it in. So this is all our own database at this point that we've pretty good on saying it's not hallucinating because it is now our data. The only hallucination might be in the report that you build, but it's, it's less common than not.

Okay.

Yeah, we can nerd out on it. Again, it looks so, so simple on the front end, but that was by design. Because if I've gone to, you know, uh, you know, we've used Definitive in the past and you're like, I just don't even know where to pull, or even Power BI, you're like, I don't even know where to pull this data from.. It's powerful, super powerful, but also overwhelming, especially for a sales rep that just can pull this up on their phone and just search anybody's name in there. Oh, we'll move over to the RepGPT one now. This is the fun one. This is trying to find, you know, they're all pretty fun, but this is, you know, trying to find, find former Striker reps in, I don't know, Dallas. And it'll essentially parse through, takes about 30 seconds, 30 or 45 seconds to go through this. Essentially AI at that point will build a query, push it through an Elasticsearch, through our data providers. Our data providers have allowed us to get the LinkedIn API, which makes LinkedIn now searchable part of what we're doing as well. And then from there I'll say, okay, they're looking for former, so it'll see the, the previous jobs. And then you could even start to search by the end of the weekend, better targeting on sports, better targeting on trauma, and then be able to actually pull up their contact information immediately. So we found 112 in Think Surgical in Dallas. So current role, Think, previous role, Stryker. Now let's go to Tyler's LinkedIn. Here you go. So you can do a little more research on them. Okay, I think I want to contact Tyler. Let's see if he's got any contact enrichments. Here you go. This is AOL. Here's the Stryker. Here's his phone number. Here's all that information. If I was signed in as a company and I had an open role with us, it's a one-click email. We're going to go to his Think email. You would select your role, you know, hey Tyler, would love to talk to you about distribution opportunity. An email sent directly over to him. So this is, you know, the next step of who's gonna, who we're gonna launch with now, who's gonna sell this product. And this one's been a very, very fun one. One company, it's just funny, someone either loves or hates the other one. But this one, they're like, we still need to figure out who's going to sell this thing. And that's what's been really, really helpful for us. So again, whether it's a recruiter or anyone, this whole thing was really meant to make people's lives a little bit easier in finding the distribution opportunities in an area.

So it's kind of like, it's kind of like LinkedIn on steroids where you can get—

yeah, LinkedIn search doesn't allow you to search there about this will by the end of the week.

We haven't talked about cost, but what's the subscription cost for the Surgeon Finder and the Rep Finder?

Yeah, all in, you're still typically cheap depending on the seats. You're still typically then that base Acuity price of $25. So this is a monthly cost or an annual cost. It's either $1,000 a month or $10,000 for the year, and then it does come up with a few seats. There are different tiers and pricings when it does come down to this Encircle GTM tool.. But we did, we know that claims data is still pushed by some companies and still wanted, so we priced ourselves to be layered on top. It doesn't have to be one or the other, so still pretty cost effective in here. Oh, yeah, that's, and this one just has limitations of the contact enrichments that you can do per month. It's around 150, I believe. You can top up those credits at any time. It's also hard to go find 150 distributors if you're a regional manager in, you know, in the Southwest of the United States. So, and it resets every month for you.

So you could buy it a month's worth and just wear it out, and if you went over credits, you could buy more credits and then— yep— unsubscribe. And yeah, man, it's kind of a no-brainer.

Yeah, it's pretty cost-effective. I mean, when it's like you hear it at first, then you see it in action, you're like, man, that's actually pretty simple for us. Um, you know, we really focused on trying to say, well, find me the, the reps that are working with Acumed in Delaware. And if you don't find any in Delaware, what is the logic that happens from there? How do you cascade out? And if you don't, you don't want to cascade too far out, what's the limitations? If you find 2, should we find more? And that's been a lot of the logic that we've been building in, which allows us to also break into the about me being searchable and not just, you know, his job title, but these will be searchable too. Whoops. These will be searchable as well. Wow. So Yeah, and then the final one is who is this person? Are, you know, are they a good hire? And this is kind of our AI interviewer, and this one's fun because all you have to do— I'm going to pick on Stryker here. I'm going to click this job posting URL and take that, and all we're going to do is say, okay, well, I want to interview a candidate and see if this is the right person. I'm going to go here, I'm going to click this in. John, this is a Claude skill as well, like, that we built in. So Claude fully runs this one, is the most reproducible for being able to do complex logic, and this is all based off of Similar to the Striker Gallup, a bars and stars scoring. If it's a hypothetical question, it'll grade a candidate on that rather than saying, well, they didn't give a, you know, a time that they did this. So very focused on saying if an example is asked, how good did they do or how well of a job did they do of explaining that and then giving truly actionable information from there. Some of the questions I would not be able to do well. It's almost too challenging on some of them, but that's how we kind of look at it as this is a great way to weed out candidates that may not be interested. In working with the company. So hopefully save some, some money on the long end of not hiring the right person. Tiger, on the financial side, this is as little as $499 or $1,000 a month depending on the amount of open roles and interviews you have. And then there's enterprise capabilities from there.

So we'll look at that maybe next if there's interest.

Yeah, this is, this is moving. It'll do that. And I'd love to send over the email to someone if they'd be willing to actually give it a shot real quick. It goes directly via email. These are the questions that comes up with it, pushes you into the executing, the influencing, the relationship, and questions on the strategic aspect. How do people think? How are they going to be able to answer these? So you can click as many as you want. I'll go ahead and just use these. John, do you mind if I pick on you? Can you get your email to your phone?

Yeah, for me? Yeah. Yeah, it's my email is John @endeavor45.com.

All right, so this is going to come to you in a second. I'd love for you to open it up on your phone.

Yep, I think I flunked the, uh, striker one, so this is gonna be bad.

Send email, um, and you should receive that in just a few seconds. It'll say, um, and then open it up and just go through real quick because just because it's, it's more fun when you see that live where you're like, this is this Australian voice talking back and forth with me. It's a pretty cool one. Okay, let me see. Um, see here. While he is— while we're waiting for that to go through, I want to show you all what the actual reports pop back. Will I— well, we can do this one. We wanted to answer these very vaguely in this process. So question was for us, for sales associate for sports medicine. Where Winston is strong, brings extensive OR experience, blah, blah, blah. Um, where he needs to dig deeper, explore specific examples of territory growth and metrics he's achieved in previous sales roles. So it actually gives you some true actionable insights to, to follow up with. And you can also get it within this PDF right here. So when you go into your next conversation with them, this is right here that you can essentially read from and, and how to read this report as well. Um, you know, they were great at executing, they're, they seemed okay at relationship building. So that's kind of that. I'm wondering if I didn't send you the right email.

Well, no, let me, let me know. Uh, like I said, I'm slowly becoming my dad on this stuff.

Um, I think the email was misspelled actually.

Oh, was it? Sorry, maybe I didn't catch it.

Let's, uh, try another one.

And then it's, uh, yeah, so it'd be, uh, John, J-O-H-N, at, and then E-N-D-E-A-V-O-R. 45.com. Sorry, I didn't catch that.

Oh no, it's my fault. That's looking correct. Yeah, this one's just kind of the ones where it's that aha moment where you're like, man, this is just a really cool platform and concept. So this was— this one's got a lot of fun attention from just the smaller startups and distributors that want a little bit more data, or even some recruiters that essentially are using it to say, okay, well, we want to make better decisions of who we're pushing through the next round as well.

Yeah, and How are, how are the candidates with interviewing with a robot, right? Are they, are they, I guess, I guess they have to do it, right? They'll do whatever you tell them to do.

But yeah, you'll, you'll see it. So it's being broadly used in general technology spaces right now and widely adopted. And there's actually a lot of money that's being invested, but there's been a ton of big exits in the space as well. And so we saw it working there pretty well. What we wanted to do was then verticalize it and bring it into the healthcare space. Space because the questions they would ask were pretty generic, pretty general. It was just essentially weeding through those first candidates. What we realized is we could do probably a little bit better of a job being able to provide, bring the cost down and be able to provide good, you know, hiring data and make a good user experience. It's been pretty fun. Very soon we'll actually be able to, to take the eye contact and the voice, essentially inflection points into consideration into the scoring algorithm as well.

Behavioral science. That's unreal.

Yeah. Well, and I apologize. I don't know if I— let me, let me see the email.

Oh, it's all right. I'll, we'll, I'll pull it to my phone here.

Okay. Sorry about that.

I, oh no. Yeah.

It's just, it's a— I decided to embarrass myself publicly.

You still can. You, we can still interview. All right.

I'm only drunk at work twice a week.

Okay. So this is the email, uh, here that'll pop up and then I'll just go and click start interview. It may hear a little more robotic if it's coming through the phone like this. So it'll say access your phone. I can see myself and then—

whoops. Hi, Stephen. I'm Ari, and I'll be conducting your interview today for the sales representative sustainability solutions position. I'll ask you 7 questions and you'll have up to 3 minutes to answer each one. After I finish reading each question, your recording will start automatically after a short countdown.

Can you hear it all right?

And good luck. Tell me about a time you had to build a relationship with a healthcare facility that was skeptical about adopting a new program or service that would change their current processes.

So it's not a bad interaction like you're asking about.

You can't cheat. It's, if it's text-based, they could, you know, they could research forever.

Exactly.

It gives you, it's real time.

It's real.

I talked and I think that, I think the biggest users of this are gonna be high-volume recruiting. So either independent recruiters or recruiters inside companies that have to, they have to interview, you know, 100 people a month and vet maybe 200 or 300 a month. And it's just, it's a volume problem.

Yep.

As you can see, I'm not a great hire, so this is a 50%, but it was, this, this one has just become a very sneaky fun one out of all the ones that we have, we've built in this platform. Oh, I like it. Yeah. And so that's where we're at, you know, trying to solve the problem of how do we find early adopter physicians. And to us, it's not volume-based at all, you know, it's, it's deeper than that. It's, it's goes layers like we showed you. Then who's going to sell it? Then are these the right people to, to work with us? And so that's what we've been trying to do, pretty cost-effective, scalable. So we've been quietly launched, you know, a little bit of a stealth launch here, but we're getting ready to go live with marketing acti— marketing activities next week of the social media postings, the videos, how RepGPT works and all that fun stuff. So it's kind of where we're at now.

Mm-hmm. Are the, what am I going to ask? The surgeons. So is there an age component to the surgeons? Can you, or can you get that through when they went through medical school or fellowships?

You can, I mean, you can see when they went to medical school and fellowship.

Okay.

I guess the question would be, is it searchable if they're there? Yeah.

Yeah. Because, you know, Maloney's not on the call yet, but we often talk about go out and find young early adopters, you know, or evangelists. Don't pay them anything. And, and, you know, they're the 35 to 45-year-olds usually. Yep. They're trying to make a career for themselves.

So.

We can find them coming out of their fellowships, and that is searchable. What we are trying to do is actually make it a little bit easier of when the fellowships— like, what we try to say is, we're actually working with a French company this morning, connect with them before they graduate their fellowship because now they have their board, they have all that information. So tap in earlier. So what we're, we're really looking at, like, how do we capture the data in the fellowship programs? Is it the Vail you know, Veil Hip Symposium, the e-posters, things like that. So that's, that's a major push to try to enhance those capabilities quite a bit. Especially trying to get them before they leave fellowship because at that point now you're just in boards and collection and all that fun stuff and good luck getting anybody to switch anything that they did in training at that point.

Yeah, Zimmer is the one that started that in the '80s and '90s where they would train, they would train fellows on their total knee, total hip products and, and then they were hooked, you know?

Yeah.

Back in the good old days, they had, they had product choice. They don't have product choice anymore, but yeah, it's true.

It's very true. So yeah, that's, that was a big one that we wanted to focus on. Um, I just remember being a rep and you'd be like, oh, I hear someone's coming out of your fellowship. That's gonna be great. They're coming to your area. Next thing you know, it's like 6 months before they'll have a, a real meeting with you. And you're like, well, we're Stryker, we're a big company. Come check us out. Rather than some of the smaller ones we'd work with. But still it was just impossible at that point. So definitely focusing more on the fellowship side for the next kind of push of data after this weekend's data dump.

So any questions, thoughts? Everybody's wheels are turning like mine.

Yeah, it's very cool.

Yeah, thank you. Thank you. It's been a fun, fun essentially platform of companies to build on this one. And we've really just tried to— I mean, there's new AI enhancements each week, so I feel like our team has not been sleeping much. Just, okay, how can we make this more reproducible? John, to your point, how do we— can we get faster data and just build a better moat around what we're doing?

And we— you didn't say this, but I think it's available on mobile and laptop tablets.

Yeah, yeah, yeah. So it's the— this is optimized for your phone. It's great for the, you know, for this one. Let me just go back to the, the, the rep side of the view. This is optimized for cell phone as well. RepGPT is not, just because it's just not a great user experience when you're doing something like that and you want to be able to sit down. But this is what a distributor would see. So they'd be able to kind of sign on here and, you know, say, okay, I'm going to click on this map role. This is perfectly optimized for mobile, which I'm sorry, we didn't even go into this, but you can click on in different roles in different area. We'll click on this one, click on this Anika role, you know, distributor wanted here. Distributor can see the opportunity here, what's going on. You know, if you wanted to post in stealth, you can click one button and none of your company information will pop up. So if you're trying to replace a distributor in a location, you could do that as well. You click on the company, if there's a video, great. And then they'll just click out, you know, who are they, brings in their contact, why would you be a great fit, tell us about what you're selling, and how quickly do you think you can get a win with this product. So this is optimized for mobile as well. RevGPT is the one that is not, just because again, that's more of a sourcing. You want, you want to sit down and do that one. Yeah.

Yep.

So, well, we've got some time. I can, I know we talked about briefly going over it, Tyler, but I've talked Tyler Tiger, but don't want to throw too much. But we do have, you know, some more time with the investor thing.

We got 10 minutes if we, so the Steve and I talked yesterday, the, the biggest problem for startups is funding. They're all— everybody's raising money all the time, and money's pretty tight. So let's look at the financing circle here.

So we build a platform, it's all AI-driven, called Bakken. Bakken is essentially— imagine PitchBook or Crunchbase for the healthcare space. It's a healthcare intelligence platform. We have over 1,500 healthcare and medical device investment firms on here, from family offices to accelerators to corporate venture arms. You can click on a, on a firm, you can search by, you know, Series A investors in New York City and be able to tap into all of their information, essentially who they are, go to their LinkedIn. You'll actually be able to do the same concept as RepGPT, just one click from here. You can see their portfolio, you can even find similar companies. Oh, whoops, wrong one. That's a quality one for me just to make sure if we do see something out of whack, we can do it. You can find similar investors to this portfolio and go middle search it. You can also search for over 25,000 individual investors at any firm or any location and get their contact enrichment as well. You can run deep research on a company like PitchBook level depth. So we parse through the SEC, their public filings, all their information, but being able to properly find private company information you need you need some pretty good tools to be able to do so, then analyze what their Form D looks like. And so what we wanted to do was give this to private equity teams as well on this side. But instead of just pulling their financial data, we can now pull all of their, their essentially regulatory, their clinical data as well. So you could run due diligence on just the financials, but the clinical side aspects as well. So you can pull in their 510s, warning letters, the clinical side of things. Are you— that's coverage gap.

Are you— do you tap into the MOD database? Can you API that?

Yep, yep. Here it is right here, and you can go directly to it. Wow, that's cool. Yep. And, um, and then the people, the most cited, uh, articles, their patents as well, and the patent. And then you just put it into its own report from here. So if you're, you know, an investor that's doing due diligence, that's great. If you're a company that's getting raised, ready to raise funds, and you want to try to see what some competitors have done, there's no better way to do so. As well as this thing is growing from our database every week. We've got agents that are going through and parsing through where to actually properly find this information and, and really focusing pretty hard on, on that. You could even do 10K analysis of Stryker. You know what happened, uh, this one we have to update this one because we just added a different code into this one. This one's fully going to be run on Perplexity and Claude. Um, but it's, it's pretty awesome. We've also built our own search engine that you could search for and a list of a ton of skills that allow you to do value analysis, approval program building, 510 building, building your marketing material, the quality assurance agent built into it as well. So hey, this is, this is the rules with the FDA you're breaking, here's the suggested changes. So it is a full, essentially research, um, investor copilot tool built for a very cost-effective— $4.99 or $4.99, sorry, $1.99 or $4.99. So pretty cost-effective. Wow. For reference, LSI has a great platform. There's about 270 to 290 investors on their platform, so ours is a much bigger platform.

Yeah. So, and yours is global, where LSI you got to go sit down and talk to somebody.

Yeah. Yeah, yeah, yeah. So this one's— this is— we'll present on this, you know, in the next few weeks here. But this one has just become such an amazing tool to build and just continuously enhancing it. You've got your FDA news, your funding information, if there's anything that's relevant to what you were thinking right there. But this is pretty, pretty fun.

Hey, John, are you still— are you raising money at Overland or are you bootstrapping?

So we are— okay, I'm not on mute. So we are— we're still bootstrapped and we used some debt. So that one is kind of a separate venture. But we do have 4 portfolio companies that are approaching probably raises in 2027, late 2026. So, you know, everything you've shown, Stephen, has relevance to a lot of the things I do. That the team does. So yeah, so we, yeah, we, we're, you know, we live in the pre-seed and seed round, but those things are approaching and we're strategizing on how to do it. And this tool, it's amazing.

Yeah, we would love to. Our team is working on this one, but I'm hoping that this goes through so you can kind of see the simplicity of what it might do for your essentially teams looking for, you know, new funding opportunities. But it's RepGPT. But focused on investors. And it's really, really— this one's easier because RepGPT, we're so focused on trying to get the right company, the right keyword, the right distributor. This, if you find more opportunity, good for you, you know.

Yeah.

But also monthly subscription, you don't have to top into a, you know, a long annual contract. And that was big. We've raised— we've lived all these problems. We just realized we can, we can try to find a way to fix it with, again, just the way that AI is at the space. John, I'd love to follow up with you after.

Yep. Yeah, we should talk. I was thinking about the 2 people on my team that should be on the call with you as well. So we could set— why don't we set something up? Is the— what is this? Uh, is the investor— sorry, my screen— I've got a screen blocking what I'm looking at here. So is the— so back in—

is that the—

that's the platform for the investor searches?

Correct, correct. And it's, it's fully live now. You know, you can go to any of these and, and it's searching pretty well. You know, you pull up different people. Within here. Yeah. So you can search by different firms, you can search by location. You can't search by, you know, find me investors, at least on this one, that are angel investors, average check size, just not doable. But within, within this one, you can, but not, you know, you'll look at firms. So if you look at, you know, the amount of family offices we have, this is a big push to be able to identify more of these because they're so challenging to identify. Um, you know, and then who are they, what have they invested into, um, you know, all that information. You can enrich it live if you'd like to as well, which is pretty cool. It's an update with most recent information. The reason we did that, we don't need a huge engineering team. Well, our kind of our users are updating information for us. Pretty nice. But yeah, we're happy to have a conversation with you after.

Yeah, do you have my— you probably have my email, but I think I took it down wrong. You did. Well, either that or I didn't. I screwed it up. But, uh, yeah, yeah, you should be able to find me on LinkedIn too if you want.

Okay, I can, I can connect you guys, no problem.

Thank you, Tiger. That'd be great. But, um, yeah, that's kind of what we built, full-blown AI commercialization engine at this point, and, and then the investor side of things. And it's really all focused on how to make people's life easier in every, every aspect, whether it's fundraising or building or launching a company. So it's been, it's been a fun journey. Appreciate, appreciate the, you know, letting us on here, Tiger.

Well, it's, this is sorely needed. I mean, the, the old way of doing things is just not fast enough or not efficient anymore. You know, it's, we've got all these intelligence tools and no, nobody's using them.

And yeah, in orthopedics, I, real quick, sorry, I didn't even realize because I had my screen sharing. Doug's on board. Doug is our Balkan brand president, by the way, everyone. So Doug comes from HSS and worked at Stryker for years.

Yeah, afternoon everybody. Tiger, thanks for pulling me in. I was having a hard time finding myself the way I'd originally registered for this. So thanks everybody.

So tell everybody what you did at HSS because it's a fascinating role.

Yeah, I was— my career is very much along the same lines as you guys in the orthopedic industry. I spent more years than I care to remember at Stryker. I was also with a startup after that and then moved to HSS, kind of what all of us would recognize more as a business development role. If anybody who's been in orthopedics for a while knows that HSS has had a lot of engineering sort of influence over the industry over the years in terms of devices that it's created and so on. The problem I found was that they never really had any good way of taking those devices and getting them out to the market except going to the surgeons and having the surgeons become consultants with somebody, which is fine. It's kind of inefficient. So we developed this business development role. It was sort of a combination of technology transfer and business development and everything that Stephen just mentioned about the Bakken platform. You know, for me, working with Stephen the last 6, 8 months, I've had a free therapist because he's been listening to me with all the things that were wrong with the system or lack thereof of what we had at HSS. And frankly, it's the same at any university or any major medical center and so on. So I'm kind of working on the earlier stage of of, you know, new ideas, startups, investment, so on and so forth. And then, you know, with Stephen's background in sales and distribution, the end circle piece of it sort of fills out the remainder of sort of the life cycle of a product. And, you know, this is what he just showed. He's been very humble and almost downplaying the complexity of what's behind it and the amount of work that he put into it.

So Yeah, I can imagine. Yeah, yeah, we're pulling for you. Um, there's lots of useful tools. It'll— the market will tell you which ones are the most needed. And I like the— I like Bakken, Bakken the best, probably number one. And probably the Surgeon vetting is number two. I, I think those are the, the hot ones.

Yeah, those are fun. Well, thank you so much. Thanks, thanks.

This has been great. We'll have We'll maybe have you again for, uh, once you get more traction, it'll be— and you can give us some stories. Thanks, John.

Yeah, thank you.

Good to see you guys.

Thank you.