A Product Market Fit Show | Startup Podcast for Founders
00:00:00 · Pablo Srugo, Rahul Shivkumar, S2
[00:00:00] S0: What's your ACV today? Let's say it's 100K. [00:00:02] S1: It's in the six figures, yeah. It took us about 12 months. Like it took us like an entire year to get to a millionaire RR. Some people may not like this, but we actually try our best to do a ton of discovery before we even show a demo. And we found that to be extremely valuable. The approach of going in and just showing things actually backfires very quickly. Investors will often tell you, go hire a VP, right? But I think you really have to, and what is that VP going to do? And you almost have to do that job first before you can hire someone for it. And I think there's this general tendency to hire quickly and not do the unglamorous work. But I'd say like do it so you can actually understand it really well. You can understand why you should have a human BDR and serve like an AI, right? And like double down on those decisions. [00:00:43] S2: That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is product market fit. Do you think the product market fit show has product market fit? Because if you do, then there's something you just have to do. [00:01:00] S0: You have to take out your phone. You have to leave the show five stars. It lets us reach more founders and it lets us get better guests. Thank you. Rahul, how you doing, man? [00:01:11] S1: Good, how are you? [00:01:12] S0: Good, welcome to the show. [00:01:13] S1: Great to be here.
00:01:13 · Rahul Shivkumar, Pablo Srugo
[00:01:13] S1: Great to be here. [00:01:14] S0: So you're the founder of Assured Health. Started a couple of years ago. Just raised a $19 million Series A by Insight earlier this summer in July. We're going to jump into the episode, but just really quickly, like what's the simplest way of thinking about what you do? Like what's a simple example that everybody will understand? [00:01:30] S1: Yeah, we help healthcare organizations hire new providers as quickly as possible and get them to seeing patients as quickly as possible. [00:01:40] S0: And you do that how exactly? [00:01:41] S1: There's a set of very complicated functions that happen. The second and offer letter is sent to a provider. They have to go through a background check, a specialized background check called credentialing. They then have to get paneled with insurance companies. So when they see a patient, the organization is able to actually file claims and collect money on. And all of these things, each individually are separate processes for each of the insurance companies. So it can get very complicated very quickly. We automate a bunch of these operations using AI agents. So under the hood, agents are verifying information in real time, packaging that up, sending that over to insurance companies, following up with them, making sure that you get the quickest effective date possible.
00:01:41 · Rahul Shivkumar, Pablo Srugo
[00:01:41] S1: There's a set of very complicated functions that happen. The second and offer letter is sent to a provider. They have to go through a background check, a specialized background check called credentialing. They then have to get paneled with insurance companies. So when they see a patient, the organization is able to actually file claims and collect money on. And all of these things, each individually are separate processes for each of the insurance companies. So it can get very complicated very quickly. We automate a bunch of these operations using AI agents. So under the hood, agents are verifying information in real time, packaging that up, sending that over to insurance companies, following up with them, making sure that you get the quickest effective date possible. [00:02:21] S0: Got you. So the simplest way of thinking about it, like you're a hospital, you're hiring a bunch of doctors. You want those doctors to be able to start work as soon as possible and bill patients. All of that used to be a bunch of manual stuff. Now you have AI agents who do it for them. Exactly. Tell me for you, when was the moment when you felt like things were working finally? Like when was that kind of product market fit moment?
00:02:21 · Pablo Srugo, Rahul Shivkumar
[00:02:21] S0: Got you. So the simplest way of thinking about it, like you're a hospital, you're hiring a bunch of doctors. You want those doctors to be able to start work as soon as possible and bill patients. All of that used to be a bunch of manual stuff. Now you have AI agents who do it for them. Exactly. Tell me for you, when was the moment when you felt like things were working finally? Like when was that kind of product market fit moment? [00:02:40] S1: There was a week where my co-founder and I had four new customers coming on and we realized we just couldn't onboard them ourselves. We had to make our first kind of customer success hire to handle onboarding a new customer, deploying some of our technology and then supporting them. Like it was a breaking point for us as the founders and I think the light bulb went off being like, wait, this is actually working now. [00:03:05] S0: How big, like four customers might be a lot, might be a little, like what kind of ACVs are you talking about? [00:03:09] S1: Yeah, our ACVs at that time were probably around like $60,000 or so. They've gone up substantially since then, but back then it was a pretty big deal. It was the first, I think, five months of the company, four months of the company I think is when it happened. Yeah.
00:03:09 · Rahul Shivkumar, Pablo Srugo
[00:03:09] S1: Yeah, our ACVs at that time were probably around like $60,000 or so. They've gone up substantially since then, but back then it was a pretty big deal. It was the first, I think, five months of the company, four months of the company I think is when it happened. Yeah. [00:03:23] S0: So, I mean, the simple way of thinking that is, I mean, you know, 50K deals, not massive enterprise, but it's still going to require, especially because you're probably underpricing. So it's probably going to still require like a decent amount of handholding in terms of onboarding and support and you were at the point where you had so much demand. It wasn't a matter of getting demand. Like you just couldn't meet the demand that was right there in front of you. [00:03:41] S1: Exactly. A lot of the workflows that we were solving then and that we still are solving today are on a forward deployed motion, right? So we have templates of what some of these agents look like, but a lot of our customers work with insurance companies in very unique ways and our agents are kind of built to be reasonably unique in handling any edge cases that a particular customer has. So this is early days where we did have a lot of templates. Some of these agents had to be built by scratch for each of these customers and deployments did take quite a bit of time. So four coming in in one week does take up a lot of bandwidth. Yeah.
00:04:18 · Pablo Srugo, Rahul Shivkumar
[00:04:18] S0: I mean, it's a classic, like it's literally the classic definition, right, of product market fit, which is when there's so much pull, the problem isn't getting growth. It's actually just servicing the growth and making it happen. We're going to talk about all that, by the way. Like we're going to talk about everybody's talking about forward deployed engineer, but we're going to talk about how you're doing it. And at the end, we'll talk about two pieces. One is the BDR motion and how you set up your BDRs. You never went all in on kind of the AI BDR, which was, I think, a bit of a hype cycle kind of came and went. Maybe we'll come back, by the way, once we have like Fable 6 or whatever it's going to be. But you decide not to go that way. You made it work. We're going to talk about like real numbers, conversions, quotas, all those sort of things. And then the AI sales tactics, like the tactics you're using today to close customers, to increase urgency and how you're doing like the forward deploy motion and onboarding, which at a high level everybody understands. But, you know, when you want to bring it to practice, the same playbook is not going to work for everybody. So take me back. That's the moment you said that was like five months, that product market fit moment, five months into your journey? [00:05:12] S1: Yeah, it was about five months into our journey. Yep. [00:05:14] S0: And when exactly did you start Assured? [00:05:16] S1: We started Assured in early 2024. So I think it was March of 2024.