Finding Your Unfair Advantage Against Industry Goliaths: Interview with Happy Health CEO Dustin Freckleton

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[upbeat music] There was definitely a little bit of a David and Goliath thinking behind it. We were small compared to our other consumer competitors, so we had to ask ourselves, "Where do we have an unfair advantage?"
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And so we believed that based off of all of our experience and where our unique strengths were, that when we looked to where the industry was going, right?
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Kind of skating to the puck type of mentality, that the future of healthcare, we believed and still do, would move from generalized models of healthcare that are built on population averages towards personalized models that are built around the individual.
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[calm music] Hey everyone. In this episode of SNL, we sat down with Dr. Dustin Freckleton, founder and CEO of Happy Health.
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Happy Health delivers at home sleep diagnosis and physician-led care through its FDA cleared Happy Ring. A physician and serial entrepreneur, Dustin has spent more than fifteen years in wearable sensing.
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He previously founded Level Technologies, which brought medical grade sensing to consumer electronics and was acquired in twenty nineteen.
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He holds a bachelor's degree in neuroscience from Brigham Young University, an MD from UT Health Houston, and an MBA from the University of Houston. Here are a few topics we explored in this conversation.
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First, how do you compete against much larger established players? Second, what should you look for when hiring for a lean med tech team? Third, what does owning the full care experience stack look like in practice?
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And last, how do you build proof points at both the patient and industry level?
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Before we dive into today's episode, a quick heads up that the full MedSider interview archive has officially moved over to my personal platform at scottnelsonlive.com.
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Our popular courses are now available there too, and they're free. Speaking of courses, if you're a founder or CEO preparing to raise capital, you should check out the fundraising cohort.
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This four-week live workshop combines small group sessions with real-time feedback to help you sharpen your investor story, build a targeted investor pipeline, and run a focused fundraising sprint instead of a never-ending slog.
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You can join the wait list at scottnelsonlive.com/courses. Again, that's scottnelsonlive.com/courses. All right. Let's get to the interview. [calm music] All right, Dustin, welcome to the program. Thank you.
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Glad to be here, Scott. Yeah. Very much looking forward to the conversation, learning a lot more about, uh, not only yourself, but about kind of what you're building at Happy Health here.
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So with that said, I recorded a very abbreviated bio at the outset of this episode, but let's start there.
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Give me, like, the, the one to two minute, like, elevator pitch on your, uh, your journey before starting, uh, Happy Health or Happy Sleep. Yeah, absolutely. So I'm the physician, founder, and CEO of Happy Health.
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My background is in clinical medicine. I'm a physician, did medical school at the University of Texas at Houston. Grew up wanting to be a doctor.
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I grew up in a home where my father is a physician, and whenever he came home from work and I asked him how his day was, it wasn't, uh, "Oh, I just got off of a thirty-hour call," you know, sh- schedule, or, "I had difficult cases."
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It was always about, "I had the opportunity to save lives today."
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And to me, that was really inspiring and something that I wanted to be able to, to do as, as, as I grew up and, uh, charted my own future as a professional.
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And I remember as I was interviewing for medical school, just coming out of college, the dean of admissions at the medical school at the University of Texas at Houston, she gave just this incredible story and, you know, she said, "As future physicians, you will have the opportunity at some point in time in your career to walk into an exam room, and in that exam room will be somebody who's wearing nothing but a robe, and you won't know them other than the name on a chart, and they won't know you other than the name on your white coat.
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And when you walk in that door, they're gonna say, 'Doctor, I don't know what's going on, but please do whatever it takes. I need help.'"
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And she said, "In that moment, you will have the opportunity to lay hands on someone and heal them." And there was almost a spiritual element to the way that she described it.
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And I remember just being so inspired by the profession of medicine and the opportunity to help people, even people who you didn't know and would probably never see again, to be able to live a healthier and happier version of their lives and address and fix the things that were deeply troubling them.
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I knew that was the, the school that I wanted to go to, so I ended up, uh, enrolling in and, uh, completing my medical training at UT Houston.
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And along the way, I was pursuing both a medical degree and an MBA simultaneously.
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And this was back in the early two thousands, so, like, Fitbit was still just a little black plastic clip with, like, a USB stick, and Aura didn't exist, and, you know, very, very nascent days in wearables.
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What I realized as I went through this experience of medical training was that I could either pursue a traditional career of medicine, which was putting hands on people in a one-on-one patient to provider type of relationship to help them, or there was an opportunity that had never existed in the history of medicine to put things on people's hands, to put things on their bodies, to heal them, to enhance their intuition, to help them understand what it was that was going on that they maybe didn't realize or that they couldn't explain.
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And that really became sort of the genesis and the stepping off point for me, was involved in a translational research center where we were working closely with medical devices and bringing them out of hospital systems and academic research institutions into the mainstream.
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That's how I got my start, was that desire to help people be healthier and happier and realization that technology was getting to the point where we could transform the way that that care was delivered and do it at a much larger level.
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That's a su- super helpful overview.
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And that first company, uh, just, just to kind of set the stage, 'cause we'll, we'll certainly get into, uh, and discuss Happ- Happy Health with a, with a lot more, uh, you know, rigor over the next, you know, call it 45 minutes or so.
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But that first company that you started was LVL Technologies, was it? Level. Correct. Le- okay, Level. Okay, got it. And, and this is, is it, is it still... Is it... I, I think it, you exited it, right?
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Or it was acquired- Correct... um, gosh, what? Six, seven years ago now. Maybe, maybe a little bit longer. But that, too, was in the kind of this, this kind of sensor, kind of wearable space, too, as well? It was.
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So Level was my second company that I exited. All of the companies, the first one, the second one, and now Happy, were all focused in healthcare, in wearable technology, really in sensor signal optimization.
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This was, again, early days in wearables. Mm-hmm. And there was obviously a lot of technology that was being used in hospitals, in ICUs, et cetera. Great monitoring capabilities, but big, bulky.
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They were tethered with cords and lo- you know, they were, they were not things that could be easily miniaturized, digitized, and made, uh, useful in an at home, kind of real world environment setting.
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And it turns out that it's not only an incredibly difficult problem to solve of miniaturizing technology and making it more wearable and more useful, but also once you do that, you create a second really hard problem, which is now you have to create clear signal when somebody is living their daily life, when they're moving around, they're misbehaving, they're doing a bunch of things that cause signals to go haywire.
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And you have to figure out, how do I tease out signal from the noise? How do I separate the data which I can trust from the data that I can't?
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And how do you still use what is left to be able to help advance decision-making and understanding?
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And so each of my companies have kind of sequentially built on that core mission of being able to pull out more data, higher quality data from the human body in the real world, and present that to the person in the moment that matters so that they can do something with it that improves the quality of their life.
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Got it. And we're recording on, in, this in the back half of 2026. But fair to say, like, you've been in this kind of like wearable arena for what? 15, 15 plus years now? I mean, you- That's correct...
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a lot of, yeah, a lot of, lot of expe- experience under your belt, right? As, have seen kind of the, the boom of, uh, kind of the wearable category o- overall. But let's get to Ha- Happy Health here.
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So, um, I'm on the website now, which is happysleep.com. We'll link to it in the full writeup. But it, it's pretty simple, happysleep.com. Great URL.
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For those that have never heard of the company, give us a high level overview of kind of what, what it is. Walk us through kind of like the patient experience, what you're solving for, et cetera. Yeah.
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So Happy Sleep is a consumer-initiated, physician-led care platform for helping people to understand what is going on in their sleep and receive a diagnosis from a licensed US-based physician and get the care that they need, not to just track their sleep, but to actually be able to fix it.
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So somebody comes to our website, happysleep.com. They don't need a doctor referral. They can check out on our website, just like they're buying a T-shirt on Amazon. We will drop ship a Happy Ring to their house.
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That ring is an FDA cleared medical device that's clinically validated for at home diagnostic sleep testing. When that ring arrives, they wear it.
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It turns literally their bedroom into a state-of-the-art sleep laboratory.
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The alternative is actually going to a sleep lab where you put 60 sensors on your body, literally head to toe, with cannulas shoved up your nose and things strapped to your torso and to your toes, and try to spend a night of sleep.
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With Happy, you can actually sleep through our sleep test. It's a very low profile, very comfortable, a wear it and forget it type of device.
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And over the course of that, of the night, we record 2.8 million FDA cleared data points that your body is continuously producing.
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And from those data points, we can diagnose a number of sleep conditions, including sleep apnea, insomnia, circadian rhythm disorder, RLS, and others.
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And then in the morning when you wake up, you meet with one of our physicians to review the results of the test, to get your questions answered, to understand what's going on and what your options are, and then we create a personalized care plan with you to help you be able to take that next step in your treatment journey.
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Whether that's lifestyle changes, or if medical intervention is required, we actually provide medical programming for treatment within Happy Sleep so that you don't have to go find that from somewhere else.
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Very helpful overview. And for those that aren't familiar, Dustin's mentioned the kind of this ring-based design. It does... You mentioned Oura, right? It kind of looks like, a little bit like an Oura Ring.
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Do I have to, as, as a patient, do I have to like, do I have to get it, like, is there like s- a sizing kit similar to Oura, where I, I, you know, you, you ship different sizes for me to wear?
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How does that, how does that work out? Yeah. So we have different ring sizes, 'cause it turns out people's fingers are different sizes. Mm-hmm. And so we have two different ways to size.
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The preferred way that most people use is as actually a digital sizing experience. Ah.
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So we created a, uh, a digital sizer that is app-based where you use the camera on your phone, and we have an AI-based, uh, sizing tool that down to fractions of a millimeter can identify the morphology and the shape of your finger and the ideal ring size, and then we ship that directly to you.
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Oh. In some cases, people prefer to use a physical sizer, so we ship one just like an Oura would.
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But the vast majority of, of our customers appreciate the simplicity and the speed that comes from digital sizing and the ring that arrives, uh, couple days afterwards. Yeah. Digital sizing, I like that.
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Like, it's, uh, it, it's, it's definitely something that I wish Oura offered, right? Uh, you know, as a...
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I don't, I don't wear an Oura Ring a lot, uh, now, but, um, but any- anyway, uh, yeah, it sounds like you're kind of on the, on the, on the leading edge of, of solving for some of these, some of these pain points.
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But the test itself, is it, is it usually like one night or is, are, are most patients... Is, is it multiple nights? What does that, what does that look like? And I'm assuming, it look...
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The website looks like it's available 48... So yeah, so almost everywhere, this is entirely remote, right?
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So it's like when I'm, um, you know, sort of going back and forth and having communication with my physician, my Happy Sleep physician, that's all virtual. That's all kind of through telehealth? Correct.
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It's all in your home. You never have to leave the home.
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We ship the ring to your house, you have a telemedicine consult with a, a boarded sleep physician licensed in the state that you live in, on your own terms, on a, you know, schedule that works for you.
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It really is extraordinarily simple. To your question of the number of nights, historically, or really anywhere other than Happysleep, a sleep test is a single night. Okay.
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That's either in a sleep lab where, again, you're in a hospital setting trying to sleep with, uh, all these sensors attached to you, or there are other sleep test devices that can be shipped to your home, but the form factor is such that it's really inconvenient- Mm...
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and not something that people would be willing to do more than just once.
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It turns out that there's actually a lot of night-to-night variability in sleep, much like there is in other physiologic parameters of the human body.
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And so when you look at the published research, it actually shows that the best results from a diagnostic and, uh, kind of like predictive capacity comes from multiple nights of measurements, so you can establish an actual baseline of that individual.
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Maybe the night that I w- I took the test, I didn't sleep at all because I was in a clinical setting. Well, that's not gonna be a very relevant result to my normal daytime routine.
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Maybe I had a lot of stress at work or in my home life. Maybe I went and drank with my friends, and you know, uh, any number of things that could affect those results.
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And so at Happi, one of the things that really separates us from any other sleep testing technology on the market is we want to make sure that we have collected a personal baseline that is established over multiple nights because, one, that's gonna increase confidence in the person that we're talking to, that this isn't an, an aberration or an outlier.
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It's actually reflective of their true state. And then two, it helps us to be able to trend post-treatment to be able to show the before-and-after results with a lot more clarity. Okay.
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I've never had one personally, but I've never understood sort of the idea of this, like, this g- going to the sleep center, right? Completely different environment that y- it...
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being connected to all of these different devices, and it would seem, in most cases, that would dramatically impact, right, the diagnostic.
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You know, but I'm certainly, certainly don't speak [laughs] with a lot of experience.
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But you know, kind of putting some, some, s- rather simple pieces together very much feels like this is a far, far better not only experience for the patient, right, but much more accurate kind of like diagnosis around, you know, whether or not someone, uh, truly does have a, a, some sort of sleeping issue, sleeping disorder.
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So, so with that, with that said, um, give us a, a sense for kind of where the company's at today, current state.
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You know, we're recording this in, you know, the, the tail end here of, of Q3 '26, so for those listening kind of after the fact, like, where's, where's the company at from a kind of a commercial and, and, and product and clinical kind of life cycle?
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So from a product perspective, today we have three FDA clearances. We are the only clinically validated FDA-cleared smart ring on the market.
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Why that matters is, one, we are more accurate, and we have the data behind it than any other wearable that is out there, and probably just as importantly, if not more so, with that clinical validation and FDA clearance comes insurance coverage.
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So the cost of ownership is dramatically different for people that come to Happysleep.
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I can go and spend $400 or $500 for a consumer-grade wearable where I may not trust the results that it's giving me, or my insurance could fully cover something that has the exact same form factor and equivalent user experience but far more rich data and the actual action steps that I can take afterwards.
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We have the ability with Happi Ring, as I mentioned before, to diagnose a number of conditions, including sleep apnea and insomnia and others, with our latest FDA clearance that expands outside of just things that are measurable within sleep but also other things within the sleep window, including aspects of heart health that we're really excited about.
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Mm.
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And, uh, the ability to not only diagnose a broader set of conditions but screen an even larger one so that we identify issues far in advance of them becoming a medical emergency while they're still just urgencies or maybe just things to be aware of that I want to avoid altogether.
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Got it. Very good. So with that said, again, happysleep.com is the website.
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We'll link to it in the full, uh, the full write-up that, that will accompany this, uh, this podcast episode if you're interested in kind of going back and reading some highlights from this discussion.
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Uh, but let's spend the next 30 minutes or so kind of going back in time and learning a little bit more about how, how you got here and, and I gue- I guess the, the first question on the docket is really take us back to the Level days, and you're, you're thinking about maybe starting a new company, and you land on, on this idea, right?
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Um, what...
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And I, and I know you have sort of a personal st- personal kind of, you know, story here, uh, as well, but what, what sort of convinced you that this was the next, you know, the next company that you wanted to, to spend, you know, a decade plus now almost, right, building?
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I think the best companies come not from somebody in search of an idea but from a lived problem that you're desperate to figure out how to solve. And that was really the case for me.
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I have a very, uh, a, a checkered medical past myself, including I have sleep apnea.
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We traditionally think of sleep apnea as being something that just old, overweight males get, and clearly I, I, I may ch- check a- at least one of those boxes. [laughs] Mm-hmm.
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But, uh, I, I, I don't, I don't consider myself necessarily as checking all of them. But that notwithstanding is that this is a stigma.
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This isn't a reality, that sleep apnea doesn't know gender boundaries or age boundaries, and it can affect everyone.
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And my experience with living with sleep apnea for almost a decade before seeking treatment is very consistent with most people.
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They live their lives thinking that being tired all the time is normal, that not having energy or needing three cups of coffee is normal.
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And it's not until they get to the point that they are so desperate that they're willing to enter a healthcare system and go through what is an average of five to six months of self-directed care to find out that they have a sleep problem, that they're finally willing to do it.
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So there's a huge disease burden that people live with for a long time, that not only affects healthcare outcomes, but also quality of life outcomes.
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And for me, the opportunity and the impetus at Happi and in my professional work was really to be able to, having first gone through that process myself- Mm...
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to say if I could make this simpler so that the next person doesn't have to go so long or through that same complicated process, if they have the way to be able to figure out much sooner and much easier what is going on in their life, that that would be really an opportunity of a lifetime.
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And that is really the, kind of the founding purpose behind what we do at Happi and, uh, my own professional journey.
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I'm looking at your LinkedIn profile, which we'll, we'll include, uh, in the, in the full write-up as well. But it looks like you, you, you started Happi kind of in the, let's call it late 2019 kinda timeframe.
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Is that, does that sound about right? That's correct. Yeah. You probably know the specific date even, maybe.
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[laughs] But, but, but just to frame that up for, for those listening, kinda late 2019, you know, when you think about kinda the past, let's call it almost, you know, almost seven years now, or maybe a little slightly over seven years now, were there a few things that, that you specifically wanted to take away from your, your last company, right, at, at, at, at Level into, into Happi?
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You're like, "I, I know, like these are the one or two things that we're really gonna get right or really gonna double down on, uh, you know, in this new, in this new venture." Absolutely.
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I think they were more principles than they were- Mm... necessarily specific learnings that translated very directly from Level to what I'm doing at Happi.
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But at a principle level, I think the two things that probably were the most formative for me were just the, the understanding of the importance of grit and tolerance of uncertainty. Hmm.
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Being able to experience and thrive in the face of significant uncertainty. I tell my kids that being successful in life, you don't have to be necessarily the smartest. You just have to be a little bit like Rocky Balboa.
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It's not about being, about being the best fighter in the ring. It's about being the one who can take punch after punch after punch [laughs] sometimes in the face, um- Yeah...
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and keep getting back up and be the one who's standing in the end. Yeah.
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And that grit is something that as, as you go through, whether it's pivots within a company or growth opportunities between companies, is being able to stay with a problem long enough- Mm... to see it through to the end.
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And the reality is, and that kind of segues into the second, is the problem that you're trying to solve or, or more actually I think correctly, the ways that you conceive in solving that problem aren't always, in fact, are seldom the same at the beginning of the journey- Hmm...
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as it is at the end. And that can be really hard, at least it was for me, to be willing to make decisions without perfect information.
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But I had to learn myself to take the best evidence that I had, to make the best decisions that I could, and then take that next step forward, right? That's not a excuse for making bad decisions quickly.
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That's not what I'm saying. But what I'm saying is that that next step frequently is the thing that creates that new information that you need to be able- Hmm... to continue on your path.
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And if you can do that and then be willing to reevaluate and adjust and take that next step over and over again, that, I have found, has been the recipe for success in my own professional life, and the thing that has unblocked me from where I was previously hesitating, waiting for that moment of certainty, to be able to be willing to grow in a more kind of evolutionary, evolving way, where I'm open to new sets of information that ultimately makes me a much more successful individual and us as an organization.
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There's definitely a trend with, like, successful entrepreneurs that come on the program that talk about this idea of, like, of, of making decisions with 70% of the information, right?
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Or 80% of the information and, and, and getting comfortable with that. And I, I like to think about it almost like, you know, every...
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I think most people are listening to this are familiar with the analogy of trying to, you know, look, uh, see around the next corner, right? Mm-hmm. And it's kinda like you...
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the way you, you, you kind of describe that is, well, in order to kind of be able to see a, a little bit beyond the next corner, sometimes I have to, like, just take the next step, right? Yeah.
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I gotta get a little bit closer to the corner so I can actually peek around, and I think that that's exactly right, 100%. And, and that you're...
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just to kind of circle back around to the first comment that you made around, um, kind of this idea of grit and resilience and, um, it's so true, and I have to tell myself that, that a lot, right?
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Um, you know, is, is my, is my pain tolerance greater than the, [laughs] than, than my foes or my competitors? Or, you know, name- True... name sort of, name sort of the adversary, right, in the, in the, in the story.
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But it, it's, it's funny. I mean, um, I'm not sure if you listened to that, that Travis, uh, Kalanick interview on David Senra's podcast recently, but, um, he mentioned kind of this very, very similar thing, right?
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Like, I can't remember exactly how it was framed up in the, in the, in the conversation, but he mentioned, like, that's one of his sort of, you know, superpowers, right?
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Is like, he just has an incredibly high pain tolerance and is willing just to eat, eat more glass, you know- Yep. Yep. [laughs]... than, uh, than almost everyone, you know? And so, um, it's, it's, it's, uh...
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I, I think it's just par for the course, right? If you're, if you're building, building a new thing, espe- especially in a, in, in such a huge area, like, like, like you are, right? With, with sleep.
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I mean, it's like a, such a significant issue that's largely under-diagnosed, even with, you know, even with the, the wearable kinda category burgeoning.
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It's still, most people still don't, don't really know what to do with this information, right? So couldn't agree with you more.
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But, um, next topic I wanted to kinda discuss was, was really kind of around kinda early, early development, right?
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And you touched on this kind of, what, 10, 15 minutes ago, this, that your technology can capture a lot of data. You mentioned even, like, some, some interesting cardi- cardiovascular, um, kind of metrics.
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I'm sure probably early on you maybe had, uh, the idea that you wanted to pursue sleep, but you could have gone probably in a number of different directions here. Maybe how difficult was that?
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And like, why, you know, how did you know to kind of like, "Hey, look, we're gonna, we're gonna first start out with sleep and really own this before we kind of go try to tackle the next area"? Great question.
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For us, actually, of all the decisions that we had to make, going into sleep was probably the easiest one.
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There are a lot of other hard ones that kind of live as satellites around that, but sleep was relatively easy for us for the following reasons.
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One is sleep is now and has always been really the most requested feature in wearables. Mm. Not surprisingly, right? It's something that we all do, hopefully every single day.
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Sleep is also the most searched for health term on Google. Mm. So it's something that is deeply personal to us.
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I can live with fill in your blank-- the blank chronic disease for a decade and not know that I have it, but one night of bad sleep or conversely one night of good sleep, boy, I know it. Mm.
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So it has a very, very fast feedback loop, and it's something, again, that doesn't just affect long-term health outcomes, it affects how I show up every single day.
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And so sleep becomes that thing that people care about in their twenties and thirties and forties when energy and mental performance and kind of earning potential are really important, and it's the thing that also drives chronic health conditions in the fifties and sixties and seventies and beyond.
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So for us, we started in sleep for those reasons. It has that consumer hook.
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But for us, it's never been just about sleep itself, at least in the traditional sense of sleep time and sleep quality and sleep stages and things like that.
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It's really about what are all the other things that you can measure within that sleep window.
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And there's great research now that shows that measurements that are taken during sleep can be up to six hundred percent more predictive of disease risk.
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I'm talking about like things like all-cause mortality and cardiovascular disease risk, the things that are like causing tremendous amounts of cost complications and, and, and bad outcomes at the individual level.
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Six hundred percent more predictive when measured at night versus measured during the day, and that includes even more accurate than measurements taken in a clinical setting. Hmm.
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Again, that's scottnelsonlive.com/courses. All right, let's jump back to the interview.
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[calm music] And so what that means is that sleep, it becomes this incredibly powerful window for detecting disease earlier when there is still time to act. Hmm. And there's a lot of reasons for that, right?
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One, not surprising, everything's quiet, right? And it's dark. Hopefully, you're relatively still. These are great situations for any device, but especially an on-body device to be able to take measurements.
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But there's another advantage here is, is, is you can appreciate in that the body goes through a lot of changes as a result of things that happen to it, right?
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The conversations that I have, the stressors that I experience, the food that I eat, the caffeine that I intake, or other things that I either exposed to from a sensory perspective that I'm seeing, hearing, or consuming, these all affect my underlying physiology, and that can create dramatic swings in everything from temperature to heart rate, respiratory rate, and other sorts of things.
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But at nighttime, all of that becomes quiet.
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So now, rather than having the confounders of something that I consumed or a, a show that I just watched, now what I'm actually looking at is the core underlying physiologic processes and the relationship that all of these systems are having with each other that becomes kind of that window into whole body healthcare.
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Makes a lot of sense. And y- y- your comment around, around sleep being one of those issues that is so dramatically different than, like, a chronic disease, right?
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In the sense that, to your point, if I get one bad night of sleep, like really bad, it's like it hurts the next day, right?
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Whereas, like, some sort of nagging thing or maybe, maybe if I've got, like, a GI disorder, like, I feel it, but it's like a s- it's like almost like a methodically kind of slow, slower kind of issue that, that evolves over time, where it's like sleep, it just, it, it'll hit you in the face the next day, right?
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[chuckles] It's very, very real if you don't get very high quality.
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In fact, like, my, our, our youngest just the other night, like, uh, he's, he's, uh, he's, he's two, but, um, he had, like, a terrible night of sleep, and it's like the next day it was, like, so, so dragging.
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It's like a perfect example of what we're talking about.
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But, um, on that note, you, you decided, your team decided to build kind of this full stack play where not only are you providing the diagnostic device but also the test, the physician, that you're, you're-- it's like a cl-- whole closed loop, like, like, kind of a, kind of philosophy, which is, you know, quite different than, like, a consumer wearable.
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And I'm sure you probably early on considered even going down this consumer path, right? Like less, less regulatory burden, but less cost, faster, et cetera. Like, there's a lot of things that
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seemingly an entrepreneur likes, you know. But you, you, you went, you went a different direction.
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Tell us a little bit more about, like, kind of what, what that decision was like in, in kind of pursuing this, you know, a, a real kind of more medical, medical device play versus a k- a kind of a consumer we- uh, wellness play.
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There was definitely a little bit of a David and Goliath thinking behind it. [chuckles] We were small compared to our other consumer competitors, so we had to ask ourselves, "Where do we have an unfair advantage?"
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And in my previous two companies, we had worked with pretty much every other major wearable brand that you can think of, including the largest multinational ones, and we understood how these systems were designed and architected.
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And they were, and the reality is most of still are, designed around a consumer problem, right?
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And specifically, it's to capture a physiologic signal, it's process it, compress it into the smallest number of metrics for efficient transmission and storage, and then discard the underlying raw data.
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And that makes a lot of sense for a consumer product, but if your interest is the promotion of health and wellbeing and creating really healthcare applications, deleting or getting rid of all of that core underlying data becomes a huge gap in your ability to deliver value not only to the consumer, but to the larger industry.
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And so we believed that based off of all of our experience and where our unique strengths were, that when we looked to where the industry was going, right, kind of skating to the puck type of mentality, that the future of healthcare, we believed and still do, would move from generalized models of healthcare that are built on population averages towards personalized models that are built around the individual.
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Hmm. And it turns out that it doesn't matter if you're using traditional signal processing or today's AI deep learning type of models, the fundamental requirement is the same.
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You need enormous amounts of high-quality data on just that individual. Hmm.
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And so the approach of just dumping data as it comes and moving on really cuts against the larger opportunity as you're trying to create personalized models that have the advantage of being far more accurate and being able to predict things much sooner.
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You can't build personalized models from consumer-grade measurements. Mm-hmm. If you're only collecting a handful, maybe 10 to 20 values per night,
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there's not enough data there to be able to solve those healthcare applications. Mm-hmm.
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You need medical-grade sensing that's capable of monitoring brain and body continuously, generating millions of nightly FDA-cleared measurements, and doing that over time in order to be able to, to solve on that promise.
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Hmm. And so that, for us, was really the, I guess, the process that went behind the thinking of- Hmm... why are we willing to go through all of this additional work and headache and complexity?
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Because we saw the opportunity of what we're solving was not really just building another consumer wearable. We wanted to set out to build the data foundation for healthcare at an N of 1 level. Got it.
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And so, so your team decides to go in, all in on this pathway, but yet you have to kind of balance the idea that, like, you do have a lot of, a lot of Goliaths, right, in the consumer space. Yep.
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You need to run clinical studies, right, to justify these regulatory submissions, or to ladder up to these regulatory submissions. How are you basically able to, to kind of do, do both in a sense, right?
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Still move quickly, but yet do it in a way that's rigorous and meets, you know, FDA, FDA guidelines.
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So I think the biggest thing for us that has allowed us to be able to accomplish as much as we have against much larger- Mm-hmm...
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behemoth organizations from an employee size, investment size, you know, market size perspective, I think the single biggest lesson that we have learned, and that has allowed us to do that, is that the quality of the team matters a lot more than the size of the team.
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Hmm. We've achieved now three FDA clearance with an incredibly small team because we hire broadly skilled rather than narrowly specialized people. Hmm.
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One of my favorite experiences was actually with the FDA, where we were speaking with an individual from the agency, and they were working closely with our CTO at the time, and they commented, "That person just did for me what it usually takes teams of 30 to accomplish."
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Hmm.
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And that's just one simple example, but I think it's an important example because at Happy, our best people can cut across the algorithms and the software and the firmware and the hardware and the clinical and regulatory and really every aspect of the system.
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And that breadth eliminates handoffs, misunderstandings, the administrative layers that typically come with a much larger organization, and frankly creates a lot of organizational bloat- Hmm...
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and allows us to be able to maintain a speed and a, you know, velocity in the direction we're going, while also the rigor of being able to do it at a clinical grade level.
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Just to follow up on that, so it sounds like that's, that's pretty important kind of during sort of the hiring process, as you're identifying and recruiting folks to join, join the team. What does that look like?
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I mean, are you, are you specifically looking for more generalists, so, so to speak? Or give, give me a kind of an example of what that, that looks like pragmatically.
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So pragmatically, from a hiring perspective, right, we're hiring for a certain role, a certain job to be done, as it were.
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But our criteria in that are fairly simple, is, has this person solved this problem at least three times before? Hmm. And can they explain in detail how they did it? Hmm.
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Because it turns out that many of the problems that we're solving at Happy are not unique, right? They cut across healthcare organizations and even into other adjacent areas of technology or service delivery or whatnot.
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It's really about how do you bring these together that is the hard part. Hmm.
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So we look for people who have experience that is relevant to the specific problem that we're looking to solve, and who is involved enough at a level that they can explain in great detail what the problem was,
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how they figured out what the problem was, how they got support from their organizations to solve the problem, and how they shepherded it through to the end. Hmm.
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And simply by solving for those two things, have they done it before and can they explain how we, how they did it, has saved us, I think, a lot of headache and heartache in the hiring process and making sure that we were getting the right butts in the right seats at the right time, as it were.
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That latter kind of way, um, I mean, it sounds so simple and straightforward, but it, but it, it filters out so much noise, right, um, so, so to speak, of just asking someone, "Explain to me how you solved this, this particular problem," right?
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And, and ask... 'Cause, I mean, 'cause the, we, we both know there's a lot of folks that maybe were sort of adjacent to the problem, right?
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Or maybe supported the problem, but they really didn't lead a team or an effort of solving this very, this very either small or big, or big thing.
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And just asking that question really brings a lot of clarity in terms of like what, you know, how, how much experience do they really truly have, like, doing this specific thing. Such a great filter.
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I'm, I'm looking at the clock here. I know we don't have a ton of time. Take us to kind of like kind of this, this phase of, of commercialization, right? Um, when you think about...
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And, and remind me again when you, when... I'm, I'm not sure exactly when you first, you first launched.
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But when you kind of go from developing product, building it for clinical studies, and now at a point where you're, you're actually, uh, this is out in the wild, right?
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Someone could, could order through your site, you know, get a ring shipped to them, do the test, connect virtually with a physician.
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Have there been some interesting kind of learnings that either you were really right on, right? Your team like, you know, had a, had a really solid plan around.
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Or maybe just interesting in nature that are maybe good watch-outs for other founders that are kind of building, building products and getting ready, re- ready to sort of go, go live?
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I used to think that the hardest problems that we would solve as a company would be technology problems.
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But it turns out the thing that was, uh, b- has been most surprising to me is that the biggest problems are actually more about the friction in between each step that somebody has to take in their journey.
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You mentioned at the beginning of the conversation here your kind of interest and excitement around digital sizing. That is a, a, a response that we get very frequently, and I used to get really frustrated by it.
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'Cause I'm like, "No, I solved all these really, really hard problems- [laughs]... in clinical sensing and in algorithm development and deployment and medical device, you know, med reg space.
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Why is it digital sizing that is so interesting to you?" And, and I think the reason why is it because it is that friction- Hmm... that prevents people from taking that next step in their journey.
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And for us, it really is about a journey.
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It's about moving from, "I have no idea what the heck is going on, so I'm gonna get screened, so I'm gonna get diagnosed, so I'm gonna meet with a doctor to understand what that means.
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Now I'm going to evaluate my insurance benefits, now I'm gonna select treatment, now I'm gonna start treatment, and now I'm gonna see if that's working for me. I'm gonna follow that over time."
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Because the conditions, even sleep that we deal with, these are chronic conditions. These are things that we deal with on a daily basis.
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Insomnia isn't something you just get once and you, you know, you take a medication, you get over it. It's something that we live with.
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And so being able to reduce that friction at each step has been really, I think, the secret sauce for us, and that comes down to being able to own the entire experience end to end.
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Because when you own the entire experience end to end, you can collapse something that typically takes five to six months, like as a traditional journey, and you can do it in as little as five days.
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Because you can identify where are the drop-off points, where are the po- points of friction or confusion, the places where people get lost to follow up and they never come back, and you can solve those sequentially.
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But you can only do that if you own not only the entire tech stack, but really the entire experience stack. Yeah, certainly an advantage, right, to what you're building, right, at Appy, right?
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Owning, owning that full, that full, that full journey and that, the, the kind of the full stack that accompanies that. But I couldn't... Like, that's such an interesting story, right? Because I, I, uh...
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When I brought that up at the AI kind of sizing bit, I'm j- like, o- obviously you probably hear that a fair amount. Like, "Oh, that's interesting." We do. We do. Like, "I had to go through this issue."
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Like, it was ki- it was okay, right? It was kind of annoying to have the things shipped to me, and I gotta size them and whatnot. And it's like I could, I could just imagine, right?
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You're like, "That's the thing that you're most excited about?" Like, there's very, very cool technology [laughs] that's, like, built into this ring, but that's the thing they're excited about.
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But it, but it reminded me of, like, how important it is to, like, as much as possible, get your thing, whatever it is, right, whether it's hardware, whether it's software, et cetera, in the hands of as many users or early users, even m- maybe prior to launch, as possible in whatever fashion that looks like, because there's so many of these types of learnings that are just...
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They're surprising, right? And you could ha- you could map out the most perfect, in your head anyway, the most perfect user journey possible, but unless it's, like, been sort of, like... Unless it's in the wild, right?
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Unless it's, like, in the hands of users that are, are new and fresh to kind of, like, experiencing your, your particular product, there's undoubtedly gonna be these types of things that surface, right?
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And, you know, the, the AI sizing is a, is a, is a perfect example of, uh, of that. So I know we've only got, um, you know, roughly about, you know, 5, 10 minutes left in the conversation.
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I wanna leave enough time for the rapid-fire portion of the interview. But let's get to kind of fundraising, fundraising and, and, and M&A, right? You, you're coming off a, a pretty, pretty sizable round.
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I think that you, at least you announced the closure of it just a, just a few months ago here. I think it was, like, 70-plus million, which huge congrats. I mean, that's, like, no... If you...
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I guess if, if you're not an LLM, right, or a frontier model, hard to raise, like, sizable rounds like this. So congrats to you and your team. You're obviously onto, onto something pretty special here.
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Were there any interesting learnings kind of going from initial fundraising to, like, closing this more sizable, uh, institutional round recently that either worked really well in kind of really convincing investors, "Hey, look, this is not just another kind of consumer kind of, like, wearable type of play with a medical bent.
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This is, like, a real thing, a real medical problem," you know, to get a round like this closed?
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Like, what, what was maybe especially helpful in kind of, like, that messaging and that positioning kind of with, with investors?
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Yeah, we definitely are not in an environment today where you can raise on just a, a pitch deck and a- [laughs]... a, a series of really well-designed slides.
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It really comes down to what are the proof points that you can create. For us, our proof points live in sort of different areas.
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There's a consumer proof point, which is if given an option, is somebody gonna choose this care journey? What is their experience? Really for us, experience comes down to CSAT scores and time to therapy. Hmm.
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Are we able to help people move through quickly and in a delightful way that then leads them to want to talk about their experience and share that with others?
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From a industry perspective, it's really about how do you improve access? How do you improve costs? And how do you demonstrate better outcomes? Hmm. And so from our perspective, from a proof point perspective-
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Our focus has not really been on telling good stories or as much as it has been on building great products- Hmm... and great product experiences and letting those products speak for themselves.
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I think in today's environment, where there's a lot of interest, to your point, on AI and LLMs- Mm...
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and kind of where the, the newest frontier model and what that's doing in any industry, but including and especially healthcare, our perspective is that the future of any AI-powered platform and, and experience is the data layer that lives beneath it.
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Hmm. That data is really hard to acquire and to come by, and it's that data that ultimately fuels the predictive capabilities and the commercial outcomes of the model that sits on top of it. Hmm.
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And so for us, the storytelling has been in both the proof points at a consumer level and at an industry level, but then also being able to demonstrate how the data that we collect is so uniquely different from anything else that is out there and connecting that to actual high-cost conditions and treatment areas.
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Hmm. So whether it's sleep apnea, where 80% of people are undiagnosed and untreated, and we can move the, the care pathway from six months down to five days.
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Or whether it's blood pressure, where we just received our FDA clearance for the first and only cuffless calibrationless blood pressure device that means that nobody has to use a cuff anymore, and we can measure within one millimeter of mercury accuracy against an arterial line.
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Hmm.
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It's these type of proof points that then connect to treatment areas like cardiovascular disease, like sleep disorders, like costs that employers will experience from an e- absenteeism, presenteeism perspective that ultimately becomes the, uh, driver for valuation and for subsequent value creation.
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Huge congrats on that clearance, by the way. That's, uh, that, that's huge. I can see... And I w- I don't wanna, I don't wanna steal your thunder, but Happy Heart could be just the next play, right?
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I mean, it- Love it... it makes, it makes so much sense, right? Uh, uh, you're, you're like, "Yeah, yeah. We hear that all the time." [laughs] Yeah. No. Happy this, happy that. Yeah. [laughs] Um- We're all happy. Yeah.
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[laughs] Yeah. A lot of smiles. A lot of smiles all around. [laughs] But, uh, so hu- huge congrats. Huge congrats. Yeah. I mean, just a, a really, really, really fun journey to kind of watch from the sidelines here.
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But in the last few minutes, uh, we have, I wanna get through the, the rapid fire portion of this interview.
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But again, for everyone listening, happysleep.com is where you can go, uh, learn a little bit more about the technology i- if you're even interested in this. If you have, if you have a potential sleep disorder, right?
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Obviously, it's a, it's a super, super easy experience as a, as a patient as well.
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So, uh, I definitely encourage everyone to check out the technology, the product, the company in more detail, which we'll link in the full writeup.
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But, um, first rapid fire, uh, question on the docket is, um, when you... Le- let's fast-forward 12 months from now. Take us back to kind of, sort of back half, you know, entering Q4 of next year.
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What are you most excited about at Happy Health? I think the, the, the milestone that I'm most excited about really isn't a revenue number or another regulatory clearance.
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It's about the personal stories that we get to hear from people whose lives are generally better because of what we've built. Hmm.
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And so those milestones I want to celebrate a year from now are the thousands of people who we've helped identify something earlier, help them get the right care, and simply live a healthier and happier life. Hmm.
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It's my favorite part of what I do today, and it's the thing that gets me up every morning excited about what I do and the thing that I look forward to in the future. Oh, very good.
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Give us one lesson that you think every... whether it's pure play med tech or life sciences in general, any- anyone that's kind of operating in this space, what it, what it...
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what's the one lesson that you think, you know, they really, really need to get right if they're gonna have any sort of semblance of success in their venture?
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So there's a quote that I love, which, uh, it, it goes, "We, we do this not because it is easy, but because we thought it would be easy." And I think that definitely summarizes my experience as a serial entrepreneur.
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And the reality is, is everything takes longer and is harder [laughs] than you expect, which is why my advice would probably be do it because you genuinely love the problem you're trying to solve, not because there's some economic or, you know, other type of outcome opportunity.
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Because if you don't truly love the work and the mission, there's so much of it that very quickly it would become misery otherwise, and it's that passion that is what gives you that staying power to continue on. Hmm.
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I couldn't agree with you more. I'm su- I'm... most people are listening to this, but I'm, I'm, I'm nodding my head. It's like, it's the one thing that I, I continue to battle with sor- sort of.
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I mean, maybe that the, the best way to describe that. But like, you know, I'm sure you have lots of ideas, right? I do, too.
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Any entrepreneur, like, you know, there's v- a lot of different things kind of bouncing around in your head, and I, I... a lot of times I just come back to that.
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Is this something that I'm interested in enough to eat glass, right? To work on- Yeah... for the next, you know, 10, 15 years?
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You know, is that big, big of a problem that I really wanna, like, you know, grind through it? I mean, it's a big... it's a, it's so, so crucial, right? 'Cause that quote that you mentioned is so spot on.
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[laughs] I think to anyone who's had any, any sort of experience in a startup. Um, all right, last question on the docket. Um, rewind the clock.
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Whether you wanna take us back to med school days or maybe, you know, shortly thereafter, anything that you whisper in the, the younger, the younger ears, or the, the ears of the, the younger Dustin.
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I'm gonna kind of riff off of actually what, what you just commented on previously in, in, in my response to that.
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I think if I was talking to a younger version of myself, the one piece of advice I would give myself is to get really clear on the principles that matter to you and always make decisions based off of those principles so you can own the decisions afterwards.
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Like you said, there's a lot of things either that are going through your mind at any given point in time, and there will always be other people, right?
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Sometimes smart, well-intentioned people, sometimes otherwise, that are gonna be telling you what you should do or what you should be thinking or where you should be going.
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And you should listen to them and learn from them, but ultimately, you have to make the decision on- For yourself and then live with that decision yourself.
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And I think that's the only way because at the end of the day, especially as an entrepreneur, the path gets really difficult and really lonely at times, and having a clear set of principles gives you that confidence to be able to keep walking it.
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Yeah. Such a great way to wrap up the, the interview. But again, everyone listening, happysleep.com is the website. So much good, good insights that you shared throughout this, this, uh, this conversation, Dustin.
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I, I, see, I, I just-- like, I'm-- you obviously did a, did a fair amount of research right in advance of the discussion, but, like, super...
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Uh, it's just gonna be really fun to watch, you know, what, what you, you and your team do in the future. I think you're, you're spot on, um, and I speak, I speak about this kind of from an early wearable user, right?
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Like, early Fitbit user. Used Whoop, like, very-- in their very, very early days, et cetera. Like, there is this huge need around this closed loop system, right?
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'Cause even, even, even in the a- the era where you can, you know, punch in data and give it, you know, serve it up to Cloud or your favorite LLM, like, there's always this need to have someone like a physician actually that's, that's seen a ton of results actually say, "No, Cloud's wrong in that case," right?
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Or, "GPT's wrong in that case. Here's what you ac- here's what you really need to, to look at," right? Or, "Here's what it's missing," et cetera.
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Like, that's so, so true to anyone who's, who's, uh, who's experimented and played around with a lot of LLMs. So I think you guys are onto, onto something cool here.
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So huge congrats on, on all the success so far and wish you, uh, a ton of success in the, in the future. Appreciate it, Scott. Thanks for having me. And for everyone listening, appreciate your attention, as always.
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Uh, Dustin, I'll have you hold online real quick, but, uh, until the next episode, uh, goes live, everyone take care. [upbeat music] Hey, it's Scott again. One quick thing before you go.
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You see, I love bringing you insightful conversations with the best founders and CEOs of medical device and health technology startups.
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But here's the thing, I'd be super grateful if you could help me reach even more ambitious doers who share our passion.
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Just open the Apple Podcasts app, Spotify, or the podcast app of your choice, search for our show and scroll down to the ratings and review section.
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Leave your honest thoughts and hit that five-star rating if you think we're worthy.
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All right, enough talk about reviews. Stay tuned for another informative episode coming at you soon.
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