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- [00:01]
A
Innovation and scientific breakthroughs are great if they have an impact, but if they stay in a box or in a book, on a shelf or in a computer file, they have no impact.
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B
Welcome back to another episode of Builders. As always, this show is brought to you by Frontlines IO, Silicon Valley's leading B2B podcast production studio. If you're bringing technology to market and want to learn from your peers, we have a library of more than 1200 interviews with Venture backed founders and marketers. Where they talk, all things go to market. Of course, if you want to launch your own podcast, we offer podcasts as a service to more than 80 tech startups. The idea there is very simple. You show up and host and we do everything else. Now, with all that said, let's jump into today's episode. Today we're speaking with Colin, founder and CEO of Sleep AI Colin, welcome to the show.
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A
Hey, thanks, Brett. Great to be here.
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B
Personal question for you. How many hours did you sleep last night?
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A
Well, if I look at my phone, I can give you exactly, but it was 7 hours and 42 minutes or so.
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B
All right. Being a sleep guy, I expect high numbers. If you had come on here and said like five hours, I would have been a bit skeptical of everything you're about to tell us.
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A
Hey, listen, Brett, I've had to work on my own sleep. I mean, I can't be a hypocrite, right? And I had a disorder, you know, in fact, I still have the disorder. It's called restless leg syndrome. But I've got it under control because I use the data to help me.
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B
I'll show you this. It's maybe you kick out of eight hours of sleep. That is my reminder. My goal for this year is to increase my sleep to eight hours of sleep. So I have that by my des remind myself. And I have it all over my bathroom as well. Just a good reminder.
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A
Whoa. How's it going?
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B
It's going good. It's hard on the weekends, I would say, and we have a little one, so it's hard. But like Sunday through Thursday, I'm doing pretty good. And I'm embarrassed to say my last year average was like six hours. So get it up there. Feeling much better. When did you start to think about this sleep problem? And when did you start to really think, okay, I'm going to go build tech for it?
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A
Well, first I became exposed to it when I was very young and my first mentor, we would travel together and he asked really searching questions and we just loved the kind of intellectual stimulation and One of those questions was, what could we do in the world to the economy and so forth if we got more productivity from the eight hours that people are supposed to spend asleep? That was the question Martin posed. And so we were all thinking about that. Roll the deck tape forward. You know, maybe 15, 20 years. My dad was diagnosed with terminal cancer, and I was in the States, in Las Vegas, living in Ireland at the time. But I was in Las Vegas at a conference. I got the news and, you know, rush to the airport, get on the last flight back to Europe, rushing into the hospital, and I sat there and I asked him, look, dad, are you up for a fight? And he said he was. So then we called the best doctor within the hospital, the most senior one in. We said, look, if he fights this, has he any chance? And I said, look, he has a chance, but it's going to be a fight. So I said, dad, are you up for it? And he said, yes. And actually, he survived that diagnosis 14 years. And a big part of the reason why he survived that diagnosis, he believed, was his approach to sleep. And I agree, too. So when I saw the effect that could have personally to the person that, you know, was closest to me at that time, my father, I actually believed that sleep can drive better outcomes for everybody. So that's the meaning, and that's kind of why we get out of bed every day, because the reason is to help people get just a little bit more sleep. And it isn't always going to be possible to get that two extra hours to get that eight hours. But let's get those extra minutes one by one by one. We win them back. And every minute matters. So I guess that's the backstory in short breath.
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B
And I'm sure you're aware of Brian Johnson and all of the crazy stuff he's doing. I follow a lot of his work. It all goes back to. I've listened to probably 20 podcasts where he's on it, and they always ask, like, what's the one thing that you can do? And he says, sleep. And, you know, he has all this crazy tech, all these crazy things, but what he wants you to do is just get a good night's sleep. So I think you're definitely on to something here.
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A
Yeah, look, when I was starting out in this business 16 years ago, sleep was for wimps, right? You know, you can sleep when you're dead. That's the attitude. But we've always believed it was important. But often, as I met people, they would say, well, which is the chicken and which is the egg? You know, does sleep cause chronic disease or does chronic disease cause poor sleep? And the reality is it's bidirectional. But there is no doubt 16 years later, with all of the research that's going on, the new imaging and the new techniques for finding out what's going on inside your body, we know for sure that poor sleep causes poor outcomes in almost every area of health and are beginning to understand more about the mechanisms of action that make it so. So at the end of the day, you know, you just think about it. When you were a kid or I was a kid and most of the listeners were kids, if you got sick, your mom would say, let's sleep it off, just get some rest. And actually, you know, the science supports that really, really, really well. And if you've got a big problem, you can't quite resolve it, don't stay up till 2 o' clock in the morning muddling over. Try to take a break. Because actually when you arrive back, your perspective has changed and sleep is what powers that. So, you know, it's not like it's a new idea. We've known this in many ways for years, but we now have the science behind it. And that's why, as I said, every single minute matters.
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B
Yeah, the science is there. And also, as you were kind of, I think, alluding to, like, culturally, there's a shift now where it's like, no longer this badge of honor. Be like, I slept five hours or I slept four hours. Like, if people say that, that's like, are you okay? It's not like, wow, I'm so impressed.
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A
Who wants to walk into a meeting of all your colleagues or go onto the football pitch with all your teammates and say, I'm happy to be the weakest player on the team because I didn't actually get my sleep. Nobody wants to do that. Right.
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B
I think the problem here is pretty clear. Sleep is very, very important. What's your solution? How are you building technology to address this problem?
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A
Yeah, in essence, it's a very, very simple idea. Again, look, if you want to manage any problem, you have to measure it first. So essentially what we've been doing is collecting vast amounts of data initially with our own proprietary technologies, which are gold standard, which are probably to this day still the most widely published and highly respected ways to measure sleep outside of the sleep lab. Because we're not going to get the 4 billion tired people into a sleep lab. It's going to cost too much and take forever. Right. So we have to bring the technology out to their homes where they sleep. So collecting the data from their phones, from their wearables, and when there's gaps in those things, collecting and predicting what's happening from other sources, that's really critical because once we understand how a person sleeps, then we can figure out, well, what do we need to do to solve it? And in solving it, we need to understand, well, what's the root cause? For some people, they can't get to sleep. That could be related to stress, but it could also be related to a boiling hot, humid bedroom, right? Some people can't stay asleep, and there are many, many causes for that. Other people toss and turn a lot, like I have restless leg syndrome, for example. So there are many issues. So what we do is we measured sleep and then understand what's happening and why, you know, did the person exercise, is it diet, is it stress, is it caffeine, is it alcohol, et cetera, et cetera. Once we understand what it is, what the issue is, and what's the cause of it, then we can do something about it, right? And so we built an engine that improves sleep at scale by collecting data that we can rely upon and trust, using that to understand the root cause, and then connecting people to coaching or to screening for disorders or to products and services that we know from science can actually help them. And that's end to end, all about the data. So it's about the data and the insights. Now, the trouble with that is you have to have a lot of data, right? So just think about me and my own record on my sleep score, for example, and I feed my Apple Watch data into that, too. I collect for me half a million data points a year, right? Just for me. So you can imagine walking into your doctor and saying, hey, look, here's my phone. Here's half a million data points and an Excel chart. Will you tell me what I need to do? It's too hard, right? So there's an abundance of data, but we need to actually turn that into intelligence. And so that's what gets me excited about today, because we now have tools to help us to do that. Machine learning, AI tools, et cetera, enable us to extract understanding from the data so we can help Brett or Colin or anybody else to solve their problem. The last thing I'll say about sleep, which. Which means that large amounts of data are critical, is that there is no one single silver bullet for sleep. You know, some people have a disorder. If they have a disorder, it's vital they go to a doctor and get it treated. But even when they're treated, if their room is too hot, if their stress, if the stress is too high, if they drink too much alcohol, they still won't get the best outcomes. So actually, you know, one intervention can be. It may be necessary, but it's often not sufficient. So that then goes back to the data. What's the data telling us? How is this person sleeping? What's the likely cause or multiple causes? And what do we need to do to solve the problem one by one by one? And then, of course, the beauty of it is when you have the data, you can confirm that your assumptions were correct, that your model is working. And that's what it's all about. It's being. It's having enough data you can trust understanding what recommendations to make, implementing that, and measuring the effect. And once you can do that over and over and over hundreds of thousands of millions of times, then you build an engine that you can be confident in.
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B
This show is brought to you by Frontlines Media, a podcast production studio that helps B2B founders launch, manage and grow their own podcast. Now, if you're a founder, you may be thinking, I don't have time to host a podcast. I've got a company to build. Well, that's exactly what we built our service to do. You show up and host, and we handle literally everything else. To set up a call to discuss launching your own podcast, visit Frontlines I.O. podcast. Now back to today's episode. And what's the business model look like? How do you monetize sleep?
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A
Oh, well, I mean, there are many people monetizing it in many ways. For us, we're doing that in. In three different ways, all of it B2B focused, because we decided we don't think there's any company on earth that can solve human sleep alone, right? There isn't, because there's too many interventions required, too many potential, you know, diagnosis on the medical side. And no single solution, as I mentioned, is enough to solve the sleep for everybody. So what we've done is build a platform that connects to all of them. And so, first of all, with our platform, we provide data to companies developing products. So we support R and D because, you know, how do you know your product works if you've never measured it? Right? And you will be surprised. There's a $100 billion sleep market out there. There are somewhere in the region of 10,000 separate SKUs and products, and so far, probably no more than 300 of them have ever been measured scientifically in terms of the effect they have on people's sleep. Right. So what we're doing is solving that problem by bringing data to R and D and developing solutions with companies so that they have products that they can market with work, and so the consumer doesn't have to go around and try all these different things, hoping they might work and not really get anywhere, which is, you know, one of the big problems. So R and D is the first business model data to support it. And the second one is we built an engine which collects data through an app and delivers personalized advice. And we've now got that fully reimbursed in Germany. So 74 million people in Germany can download and use that Dien Schlaf by Sleep AI app, and their health insurer must pay for it by law, without the need for a doctor's prescription. That's a huge breakthrough.
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B
Wow.
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A
Because the German government gets it. Look, we cannot afford. None of us can here in the United States, all over the world, nobody can afford the cost of health care for a sickening, aging population. So we have to start investing in preventative measures early. And if we do, we can help reduce the downstream risk of pretty much every major chronic disease from dementia to cardiovascular disease. So the Germans get it, and they're the first in the world to do it. So we basically package the solution that's then marketed by their insurance companies to their members. Second business model, but the last one, which I think, to be honest, is the biggest one and the one we're most excited about. And I think that some of the founders on this, listening to this podcast, will have a need for it. We've compressed everything we do into a simple SDK and a suite of APIs so you can put better sleep into any app. Now think about that for a moment. If you want to help a person to lose weight or to get fit, or to conceive a baby or to manage diabetes or to deal with some chronic health condition, you cannot be successful without sleep. You must have sleep, but it's too complicated for you to work that out. You're already a specialist in each of those areas. You know your business, you understand the relationships, but you don't understand sleep because it's too complex. So we provide that in a very simple API and SDK so that you can empower your users. It engages them more because they sleep every day. So you have something to talk about every day. And most importantly, it substantially increases the outcomes that you can achieve with them for their health. And think about that. Our goal is, we want to reach and touch a billion or more people through those SDKs and APIs, because that's how we really make a difference. Going back to the mission that we talked about at the very, very beginning, we make the technology available to everybody and all they need is a smartphone. If they have a wearable, that's great, we'll take that too. But whatever it is, we just need to start a smartphone at minimum. And that enables us to scale up the reach and the effect that we can have with all of this research we've been doing.
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B
It seems like you have to be in the golden era for this, right? In terms of just consumer health devices. Like, I'm wearing my whoop here. I have my levels, CGM here. I have a throne toilet. You know, all these like, things. And I feel like everyone I know you're given, like I'm in San Francisco, so I feel like a lot of that tech is like everywhere. But everyone I know is buying a lot of tech right now and using a lot of tech and everyone's obsessing about health. So it seems like it's a perfect time for you to win that market or go after that market.
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A
Absolutely. And look, we're the sleep guys within this and we connect to the data sources. We are agnostic as to whether you want to wear a whoop or a ring or nothing at all. We're agnostic because really we're not trying to sell a measurement system. What we're really doing is using the data intelligently to help people achieve better outcomes. And in order to do that, you have to have hundreds and hundreds of studies behind you. And the key issue here is the data and the studies and the science. And so we've focused on that most. And then our strategy is we work with all those great companies that have wearables or have products that improve wellness. And let's add sleep to that because that's going to turbocharge the outcomes for everybody.
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B
And what's the go to market motion look like? Maybe let's just focus on that third one that you were talking about, since you said that's the one you're most excited about or the biggest potential.
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A
Yeah, well, look, on our side, we've only really started going to motion, sorry, going to market in the last kind of nine to 12 months. So we've been building this platform over eight to nine years, and it takes that long to collect a billion hours of data and to connect to more than a million people and to publish 100 studies. So we put all of our effort into doing those things first. Along the way, we actually built business because companies with real problems where they were trying to get better solutions actually found us and came to us. But now we're shifting gears. So we're shifting from literally no marketing and nearly no sales resources to a company with marketing and sales. So what we're doing, first of all, I think, is we're telling our story. And you know, to be honest with you, Brad, I come from Ireland, right. And we're. Culturally, it's amazing how similar we are, but it's also amazing how different we are. So in Ireland, you kind of culturally, you don't start to brag about something until you have it. But I do know that there's also fake it till you make it. And it's a valid strategy. Right? But we just couldn't do that. I can't do that. I just can't do that. So what we decided to do was to build it, test it robustly, make sure it was working, small number of clients, and when it was ready, then announce it to the world and then start to share our story. And, and that's what we're literally just started doing. So we have, you know, marketing resources. We're showing up at events and meeting more potential partners. We're reaching out to those partners. We're actually building referral programs between our existing customers to help us find more partners. And we're also partnering with different companies in the ecosystem. So we've, you know, hired sales and marketing resources, PR resources and sales resources for the first time. And all of that's getting built out. So, you know, that's, that's, that's something which is clearly critical for us to scale and grow. But it's also something that we had to learn how to do to add on to our kind of deep science and deep data moat. But actually being able to bring it to market, that's a whole new focus within the company and something that we're testing and learning and getting better at every week and month. This show is brought to you by the global talent company, a marketing leader's best friend. In these times of budget cuts and efficient growth, we help marketing leaders find, hire, vet and manage amazing marketing talent for 50 to 70% less than their US and European counterparts. To book a free consultation, visit GlobalTalent
- [17:10]
B
co. Years ago, I worked with a company that was doing. They were a material science company and the company ended up failing. They went bankrupt. But, you know, they'd raised like 500 million. They spent, I think, 15 years in R and D. And basically I was. Or the CEO, I was talking to them afterwards, and he said, like, they just couldn't change the culture of this, like, R and D science culture to like a commercialization culture. Is that something that, like that you think a lot about, of changing culture?
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A
You know what? I'm working incredibly hard not to change the culture. And now just bear with me for a moment because I think it's all about why people are motivated to work with you in the first place. Right. So what I like to say to our team is, look, innovation and scientific breakthroughs are great if they have an impact, but if they stay in a box or in a book on a shelf or in a computer file, they have no impact. So our responsibility is not only to make it, build it, and make sure that it works and build a science around it and so forth. Our duty is our duty. Once we know how to use an insight to improve people's sleep, we have to get it out there. So our scientists talk to our customers or our prospective customers. They're part of the sales process from the beginning to the end, because that is the culture. The culture is not about, you know, investigating for the sake of it. The culture is we have to have impact. And how you do that is you reach people through partnerships and make their lives better by helping them to sleep better. And if you do that, that's the right culture. So, you know, so where I come from is once everybody understands that everybody in the company's got an inverted. Commerce has a role to play in the sales process because that's how we reach people, then it's not actually a difficult thing to have people continue to do. Even though deep down, though, everybody also knows that there are things we will not do. We will never, ever, ever sell somebody's data because they don't want us to. And we've agreed not to. So we will always honor our commitments. We are never going to be an ad platform because we don't believe in promoting something that we don't have scientific evidence around. So we could make a quick buck sometimes in a few areas. But our focus is on to actually make the impact and do it at scale. And we want the end customer to be able to trust what we do and to trust the recommendations that we make because they're grounded in science equally. We know that we have to get out there or we won't have any people to improve their lives. And so that's the adjustment to this. Starting with the science only. I think we're starting with the science, but we're starting with the science and the belief that we must, we have almost a moral imperative to use it to improve somebody's sleep. If that makes sense.
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B
Makes total sense. Now, final question. I know we only have two minutes left. Let's talk about the big picture vision. Where do you go from here?
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A
Yeah, look, we want Sleep AI to touch a billion people or more through the companies that they already reach by being their trusted sleep partner. And then we can connect, then we can begin to connect the dots because we have the data, we have an understanding about how a person sleeps, but we also understand what products and services affect that. And when we connect those sets of dots, which we are now doing, we really add value. Because who wants to go out and shop for solutions if they don't know whether they work or not? What people want is they want help to sleep better. And by connecting the dots, we think we can do that. So in a few years time, I think what you'll see is you'll see vast access in terms of distribution and you'll see a vast number of improvement services that we can offer. But you can always rest your mind one thing. You will always know that you can trust it because there's robust science behind us.
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B
Amazing. I love it. Love what you're building, love the problem that you're solving and I love the approach that you're taking to solve it. Now, before we wrap, for those listening and that want to follow along, where should we send them? Where should they go?
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A
Oh, cool, there's www.sleepa.AI. so sleep AI. And you can also find me on LinkedIn. Colin J. Lawler. C O L I N J L A W L O r or sleep AI on LinkedIn too. And look, we'd love to chat with you.
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B
Amazing, Colin, thanks so much.
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A
Thanks, Brett.
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B
Well, that's all for today's episode of Builders, brought to you by the Frontlines. If you want more amazing content like this, visit Frontlines IO where you'll find the library of more than 1500 interviews with founders, marketers and other GTM leaders, where we unpack the tactical lessons from their journey. And of course, as always, if you do want to launch your own podcast, we'd love to have a conversation with you. Visit Frontlines IO Podcasts as a service. Mention that you listen, mention you love the show, and we'll give you a 10% discount. Thanks for listening. We'll catch you in the next episode.