The Melanie Avalon Biohacking Podcast Episode #324 - Jason Moore

TRANSCRIPT

Jason Moore
we can get really accurate readings of heart rate, HRV, respiration rate, and a full body composition analysis now using literally just the phone that you have in your pocket or on your desk. There's a difference between measuring and estimating.

Almost all the metrics that we all use today are estimates, not measurements. Other than really dramatic changes in your hydration, DEXA can be thought of as a very accurate and reliable estimation of body composition.

Melanie Avalon
Welcome to the Melanie Avalon Biohacking Podcast, where we meet the world's top experts to explore the secrets of health, mindset, longevity, and so much more. Are you ready to take charge of your existence and biohack your life? This show is for you. Please keep in mind, we're not dispensing medical advice and are not responsible for any outcomes you may experience from implementing the tactics lying herein. So friends, are you ready to join me? Let's do this.

Welcome back to the Melanie Avalon Biohacking Podcast. Friends, I had such a fun time in today's conversation with Jason Moore. I cannot recommend his Sprint app enough. It is such a cool way to instantly get a highly detailed overview of your body composition comparable to a DEXA scan in your own home with just two pictures.

It's wild. You'll find out your true fat mass, your true muscle mass, so many things. And you can get a free trial as well as 50% off your first month with the coupon code Melanie Avalon. For that, just get the Sprint app. That's S-P-R-E-N in the app store. Use the code Melanie Avalon for a free trial, 50% off. Not only will it make it so easy to get overwhelmingly detailed body composition reports comparable to a DEXA scan, it also can measure your heart rate variability, provides AI coaching, helps you make change, and so much more. And in today's conversation, we talk about so many cool things. We talk a lot about the future of health technology and the role of AI in that and whether or not you should be worried about AI. We talk about the role of HRV and health and wellness, what to do with data overwhelm, the importance of context, feedback, and outcomes, the role of testing your health biomarkers, the role of awareness in making change, and so much more.

The show notes for today's episode will be at MelanieAvalon.com slash Sprint. That's S-P-R-E-N. Those show notes will have a full transcript as well as links to everything that we talked about, so definitely check that out. I can't wait to hear what you guys think. Definitely let me know in my Facebook group, IF Biohackers, Intermittent Fasting plus Real Foods plus Life. Comment something you learned or something that resonated with you on the pinned post to enter to win something that I love. And then check out my Instagram, find the Friday announcement post. And again, comment there to enter to win something that I love. All right, without further ado, please enjoy this fabulous conversation with Jason Moore. Hi, friends. Welcome back to the show. I am so incredibly excited about the conversation we are about to have today. So it touches on so many topics that we talk about on this show, as well as a lot of things happening in the world just right now in general and some avenues to truly optimize monitoring and taking control of your health. So I am here with Jason Moore. He, well, he does a lot, which I'm sure we're going to talk about. He works a lot with AI type technology in the health world to actually help with body scanning devices.

Melanie Avalon
So things like getting data that you would get from a DEXA scan or figuring out your HRV. And we're going to talk about this in the episode, but he's developed a lot of that technology. He also has an app that specifically showcases this technology, and I actually tried it this week. And it is so cool.

You literally can do a DEXA scan at home or the equivalent thereof. So we're going to talk all about that. And when I reached out to you guys, I got a lot of questions about apps and wearables and HRV and all the things. And as you guys know, I am really, really passionate about monitoring your health and seeing what you can do there. So I am so excited about this. I'm also excited, Jason, because I mean, you come. Well, I'll let you introduce yourself, but I'm really excited to hear about your technological background. And because I feel like most, I mean, I have a lot of guests on this show, but oftentimes it's like authors and doctors and researchers. It's rare that it's somebody, you know, really in the tech world. So thank you so much for being here. I have so many questions for you. And yeah, I'm excited to jump in.

Jason Moore
Awesome, Melanie. Yeah, hey, I'm excited to be here.

Love what you're doing, love the messaging that you're getting out there and educating people on and happy to dig into whatever would be helpful to people.

Melanie Avalon
Awesome. Well, I will say we have something in common.

I was reading through your bio and you mentioned one of your, actually, I guess the only name you mentioned, person's name you mentioned is an inspiration is Rob Wolf. He's literally also like a main reason I'm doing what I do today and because I read the paleo diet and you're linking him to things like CrossFit and such, but yeah, when I had him on the show a few times, it's just surreal to me. But speaking of your personal story, health, tech, chicken or egg, like what? Where did your journey start and did you see yourself ending up doing what you're doing today?

Jason Moore
Definitely couldn't have predicted my path, including my crossing of paths with Rob over the years and others that I've learned so much from. I mean, basically what best describes me is I am a nerd through and through. I love to learn things, I love data, I love tech. I built my first computer when I was six years old with the help of my dad who was also a technologist and learned how to do early programming when I was like 10. And so super nerdy.

And then I also thankfully went outside every now and then and played sports growing up and kind of stalled out on my own performance around my early 20s. And so that's when my parents had always talked about like, oh, we need to eat healthy and we need to do these things, but they were kind of operating a little bit in the dark. They didn't have, like we do, where we can just listen to these amazing podcasts that are full of such deep information. And long story, not so short, I found a way to kind of get more deep into the health and fitness space out of passion and then marry my tech background with it, which I can go all into the weeds on if you want, but that kind of led to the genesis of this company, which then led to this kind of crazy journey of working with top pro sports teams, working with the military, police, fire, kind of pushing the boundaries of what we can learn from our body. But then we had this kind of almost like counterintuitive mission throughout all these high performance relationships to make this stuff more accessible to just everyday people.

And I kind of come from, I guess you could say, a very normal family. So not like tons of money in our family and instead tons of health issues. And we kind of as a family check all the boxes of all the major health killers really close to me. But like to be active and do things and have fun and enjoy life and appreciate the performance side of it too, mental and physical. And so yeah, that's kind of been some of the DNA of the company has been like, how do we take what billionaires and pro athletes have and make it available to every person while keeping the quality really high?

Because as a data nerd and sure people listening now, garbage in, garbage out. And so that's kind of led to a bunch of innovations and then investors getting involved. And yes, like I said, I feel like in some ways I'm floating down this rapid river and I'm just trying to like keep up with it all and it's exciting. But thankfully having that base of health and performance in my own personal life has helped with the juggle. And I feel like was one of the things looking back to Rob on in the early days, he was big inspiration to me. And I could not have done all of this without making some of those early changes to my diet, my lifestyle, my sleep, my stress management and been able to perform it at the level that I've been performing. So in any case, that was a bunch of stuff about me. Where would we like to go next?

Melanie Avalon
I feel like growing up, okay, so I was a big nerd. I loved Star Trek.

I actually was in the computer programming club at my school. I think I always wanted to be like a programmer and my parents were programmers, but I actually never like learned it or did it. So like in the club, for example, we actually traveled for like competitions, but I didn't actually do any programming. I just created the like creative aspects of it.

So like, it's funny, you have a skill. What I'm telling you is you have a skill that I like always wanted and never achieved.

Jason Moore
The creative aspect is super important. I have to say as humans, like anyways, programmers do not often relate to people as consumers and as people on their health and fitness journeys.

And so connecting the dots to creativity and art and communication and, and like how to actually apply all of this stuff that we can build is I would say equal, if not more important. So.

Melanie Avalon
Amazing. Yeah, I remember the competition was to create a game, but it was a text based game. So I was like, I'll create the like, these physical, like the assets that come with it, like, like the instructions and the maps and things. That's so funny.

Oh, wait, speaking of programmers, I was listening to a podcast last night. And they were saying that there is a discouragement today for people to become programmers, because AI will be able to all programming. Do you have thoughts on that?

Jason Moore
Well, so, I mean, probably yes, but not, it's, I don't think it's that simple. Learning how to program, for one, people who don't do it may not realize, but it is a craft that feels like you're building something, it's like paint, doing a painting or building with Legos or, you know, something like that, that is a little more relatable to an enjoyable craft. Programming is that for a lot of people. And also it has this big upside of problem solving and math and solving, you know, hard things, and so all, for all of those reasons, I don't think any of that, the need for problem solving or critical thinking or working hard on something or refining a craft, all of those things are positive that are not going away.

So if programming is that outlet for somebody, I would highly encourage them to just pour themselves into it. And whether that job is going to be the same for everyone over the, even the near term, to be honest, I would say it is going to change quite a bit. So I would, as a career outlook, pair that with sort of continue to refine your understanding of the universe and how, you know, value flows between people and all of these types of things. And that will elevate your career path no matter what, whether programming is or isn't a human activity for money.

Melanie Avalon
You know I love that perspective. I'll tell you my concern if we don't have any human programmers, then what if one day we none of us actually know how to program and if like if AI is completely in control.

I don't know. I'm just concerned I mean.

Jason Moore
Yes, that is, I mean, that's a valid concern. And I'm for sure, I'm not like a geopolitical expert on that.

But I would just kind of my simplistic view of it maybe is kind of liken it to food systems, right? Like 100 years ago, or maybe a little bit further, 90 plus percent of people knew how to grow or find their own food. And now 90 plus percent of the population has no idea how to do that completely dependent upon a system that's out of their control for basic sustenance. And, you know, that would be really weird if you went back 200 years and said, hey, we're going to do this thing that makes it so no one knows how to grow or find their own food. It'll be better, we promise. And, you know, people would have been probably it wasn't quite such a conscious reckoning as maybe AI taking jobs is. But anyways, I thought that that was kind of an interesting parallel when you said it. That's the first thing that came to mind.

Melanie Avalon
It's such a good example. It's actually, and the thing that comes to mind from that for me is I've recently been looking at my, like my personal business and what I can outsource more, you know, to other people and delegate and things like that.

And there's, it's really scary to give up control and then also realize that you no longer, like you're really relying on other people to do the systems. But I feel like that's, I guess that's the nature of evolution. Like in order to really evolve and, you know, go, go far, you've, you've got to let go, but then you are relying on third-party things. I just need to make copies of myself. Really helpful.

Jason Moore
There's probably an AI solution for that. The challenge too is that food is such a universal need, at least it has been historically. And we collectively kind of trust that as a people, as a species, we're all going to prioritize that.

Whereas AI kind of concentrates power in a and so that is kind of where some of the... I'm a tech optimist and I think there's a lot of amazing benefit that we can get from technology. But I do think that it needs to be kind of carefully looked at because it's not quite the same as saying like, hey, we're all going to agree to work together on food so that we don't all have to be farmers. It has higher upside and higher risks, potentially.

Melanie Avalon
Actually, so here's a question for you. And I realize, well, I'm trying to decide if we should have a more foundational conversation before I ask this question, but in all of the, the AI that you've developed with your companies, and we can, we can dive into those.

Have you ever had any like really shocking moments with something it did?

Jason Moore
I mean, well, let me think about that. So we have been an AI company, and we've been using AI long before chat GPT came out. And some of our early core innovations were actually shocking to us, in the sense of what it could actually do, what kind of things it could pull out of a noisy signal, for example, and we can get into that aspect of it. More recently, as we've kind of connected these data streams to the AI that lots of people think of, like chat-based or conversational-based AI, you know, our scope is a little bit more narrow than a general chatbot. So it's potentially less interesting to talk to about like which movie to watch, for example, than like a chat GPT or something like that.

But it can go really deep on your data, and it can pull insights out that it doesn't seem like it would normally have the core competency to do. And we can get into that too. Those are kind of luckily, those are both very positive surprises. So we haven't had any like big controversies of it saying, you know, there's this meme going around about one of the AI systems telling people to like glue their pepperoni to their pizza or something like that, you know, something like that. We haven't really had anything like that. And partially, it's probably because the narrower scope, but also, we're just really focused on specific outcomes for people. So the surprises have all been pleasant, which is great.

Melanie Avalon
That's awesome. Yeah, I guess it's important to distinguish between, you know, the type of AI that is crunching data and numbers versus the language models that are communicating with humans about it and translating it.

So, okay, questions. Being in the biohacking sphere, I have always been really interested in data collection and, you know, back in the day before all the apps, I was making Excel documents that were, you know, oh gosh, I'm getting flashbacks right now, like so long with like all the supplements or like my sleep data and, you know, trying to make sense of everything and everything became much more easier as different apps came out and, you know, and things like that. It can be hard to know because you mentioned at the beginning you were talking about how, you know, all these different biomarkers we can test and, you know, things available to elite athletes that, you know, other people might not have access to. I think it can be very confusing knowing, A, what to test, B, how often to test, C, the validity of these tests. So, when you set out, you know, to create these different systems, like where do you sit in the world of what people when it comes to their health should actually be testing and how often, like, what clarity can you provide people there?

Jason Moore
Yeah, yeah, no, this is great. I mean, it's also a very natural question because there's so much, right? And I kind of think about this through the, and this is partially what, as again, kind of a tech nerd makes me fit in so well with the AI space is that there's kind of three elements. One is context, two is feedback loops, and three is the outcome that we're seeking, right? And so if I kind of work backwards from the outcome, is it the relief of pain? That's actually a big reason why people get into health and fitness or biohacking or other things is basically they're trying to relieve some sort of pain, right? And the good news with that is that oftentimes, depending on the type of pain, the feedback loop is pretty clear. It's like, did the pain get less or more or stay the same, right?

And then there's context not only around why do you want to reduce this pain or what is your financial or lifestyle situation or who do you have supporters around you or not, all of that type of stuff, but also like what data points can you start to collect that let you know more about if you're moving in the right direction in the maybe what might work better for you that doesn't necessarily work for the next person. You've got to kind of gain this context and these feedback loops about yourself as you get more into the weeds on your health, your performance. You know, we kind of bucket these journeys into they often fall into performance, longevity, and aesthetics. And that's kind of an oversimplification, but a lot of times people's why ends up kind of in one of those buckets.

And pain kind of crosses all three of those to a degree. But so anyways, that's kind of how I think about it. And then from there, what we see, because we're in a position of providing tools to millions of people, we start to see patterns in the population also, right? And this is where I get really excited because again, as like avid learner and curious person, working with the community earlier, you asked me about surprises from AI, I've had far more surprises from people than from AI about all the things that they can do when you give them access to data that was not previously available to them.

And when you make it cheaper, more convenient, and ability to interpret it and measure it more frequently, that type of stuff. So the journey started with HRV for us, because basically, I was coming out of the oil industry, I worked in tech in the oil industry early in my career, basically doing sensor data analysis and preventive maintenance on expensive oil field equipment. And we're doing a bunch of software predictive analytics and kind of essentially maintaining and improving the health and performance of the equipment. And then nights and weekends, I became a coach and then an educator, I taught courses on biomarkers and things for the National Academy of Sports Medicine, NSCA, just weaving in a little bio into the story, I guess. But the point being though, is that I realized, okay, exercise, sleep, stress, inflammation, food, all of these things can be broken down into a fractal of additional layers. And then they all tie together.

Jason Moore
Is there anything we can track that really lets me know if I'm just going in the right direction or not. And HRV was the first metric that I got really excited about for that. And since then, we've added and expanded our knowledge of the space. And basics would be for a lot of people, HRV, resting heart rate, respiration rate for some cases, but cardio respiratory fitness. And then more recently for us, body composition has really exploded onto the scene, not only because people are interested in things like weight loss, but because of how impactful it is to how you feel, how much energy you have, your longevity outlook, basically every mortality and morbidity marker is related to body composition.

And that for the first time, kind of, I guess I'll unpack again, my three little pillars there of context, feedback, and outcomes. Body composition is as close to a measurable outcome as we have from sensors. A lot of the other things that we track are actually inputs. Right? They're kind of like steps or sleep or activity or food logging. These are all inputs that are all very important. But then if you can actually get a measurable outcome, or at least as close as possible to a measurable outcome, then the feedback loop starts to become a closed loop system. And then you can say, okay, are the inputs that I'm testing? And if you think of yourself as a citizen scientist, are the things that I'm doing moving the outcome I'm looking for in the right direction or the wrong direction? If not, it doesn't necessarily mean those are bad behaviors. It just may be that they need to either be combined with something else, or perhaps something else is holding you back more than this thing that you're addressing. Or hopefully you just see progress, and then that progress can keep you motivated. And you can take that activity to its full extent. And then eventually stuff runs out and you realize like, okay, if I just started high intensity interval training, that may have a huge benefit to my health at first, but then it kind of plateaus and more is not always better. And I need to figure out a way to then integrate other activities into my life now that I've got that one down. Maybe a little bit of a meandering story there, but that is kind of the genesis also of how I got into this and how I started troubleshooting and finding which metrics should I be caring about. Is 10,000 steps really the thing for me? I don't know. Maybe it is, maybe it isn't, but there's an outcome, whether that's how I feel or some markers that I can improve that will let me know if that is actually moving the needle for me or not.

Melanie Avalon
So many things. Okay, first of all, just a quick tangent.

When I interviewed Mark Sisson for his book, I learned in that book his most recent one about running or walking. Do you know where the 10,000 steps came from?

Jason Moore
No, not off the top of my head. No, I think I've read something about it once, but it escapes me. Yeah.

Melanie Avalon
This is so mind-blowing to me. So it's the symbol for it either in, I think in Japan maybe or China.

It looks like a, it was like an advertising campaign and it kind of looks like a running man. So that's how they picked 10,000. Like it's so arbitrary.

Jason Moore
Perfect. We should benchmark everything off of that.

Melanie Avalon
Yeah, just a side note there. So the HRV point that you, you know, started with and were really fascinating about as this, you know, marker to sort of capture, you know, if what you're doing is working essentially. So historically what I've used to measure my HRV is an aura ring. I've had them on the show a few times and have done deep dives into HRV.

And so actually I have questions about, about your technology with HRV, but before that, can you just for listeners who are not familiar, I bet most are, but for those who are not, can you give us a brief overview of what HRV actually is? Heart rate variability.

Jason Moore
Happy to, yeah. Heart rate variability. And basically every time your heart beats, the time between each beat varies slightly, right? An easy example is when you inhale, your heart rate increases a little bit, so it beats a little faster. And when you exhale, your heart rate decreases a little bit, so it beats a little slower. You want that, actually.

If it doesn't, then that's a problem. And what's interesting about HRV, though, is that it's easy to measure now and gives you a window into the nervous system. And then through that window, you actually can see a ton of the stuff about the body. So HRV's kind of power is also, in some ways, its curse, is that it's a very holistic metric that's very sensitive to everything going on in the body.

But big movers are your respiratory system. So like I said, breathing your nervous system as it responds to stress. So if you have a fight or flight response, or if you are more in a relaxed rest and digest mode, we can see different patterns in HRV that let us know which kind of mode your body is in, so to speak. And that is a bit of a, you know, it's a bit of a simplification, but for practical purposes, it's very powerful for seeing like, okay, you want to be in a relaxed, even recovery mode most of the time, you don't want to be overstressed most of the time.

Now that also has nuance to it, because if you lead a high performance life, then a lot of times the goal is how much can I push my limits and still recover, you know, and still perform well tomorrow and the next day and next week and the week after, right. So but HRV kind of gives us a window into all of this. And then it also is a biofeedback tool, because it's so sensitive. And because you can do things like control your breath or manage inflammation through dietary changes, even as simple as changing the timing of when you eat relative to sleep can have a big impact on your HRV.

So it lets you kind of do all these fun biohacker experiments. And for companies like Aura, which is a great product, by the way, HRV and sleep are kind of two cornerstones for them on a lot of things that you would learn by changing things that especially, like I said, impact your sleep. Yeah, it's a great tool. But then I said that I said it's also a little bit of a curse because, because it's so general and broad, you know, I've, I've worked with some of the top like functional medicine doctors in the US, for example, and they dialed in every micronutrient, every gut biome detail, and still couldn't get their HRV to improve. And usually for that crew who has so many things dialed in, the answer ends up being enough time in nature. And so you see this immediate surge increase in some people when you're not spending enough time out in nature, and then you do. And so you can go really far with HRV, but sometimes it's hard to figure out which piece is actually moving the needle and it takes some experimentation.

Melanie Avalon
Oh, wow. Okay. That was really exciting to hear something really concrete like that, that has been found with people who are really, really struggling.

Okay. So my, this is like a concept that haunts me perpetually because I agree so much about time and nature. There's so many aspects to it. So the, the light exposure, the grounding, the, you know, just getting out of our modern slightly toxic environments at the same time, I actually, I don't like going outside normally. So I don't really like the elements that much, definitely not in the summer. So I, I kind of exist in this place where I'm haunted, where I'm like, I know being outside, like I wish I was, some people just love being outside. Like my sister loves being outside and I just don't. And so I struggle with this concept where I know it's really good for me, but it doesn't appeal to me that much.

Jason Moore
Well, you know, that's kind of what's interesting about the making these tools just easier and more accessible is part of the story is like, okay, they're short term and long term decisions, you know, that we have to make and without the tools and the feedback loops. It's really hard to prioritize the long term over the short term, but you know, it doesn't mean that you have to become an outdoor person, right?

Similar to my example with the high performance lifestyle, you know, if you don't like being outside and you and you like a lot of other things, then that's not like inherently bad. What you might find out is that there's some threshold where you're like, I just need to get out this amount and that mitigates the downside as much as I, you know, need. And then I can just do the things that I like to do after that. And, you know, that's kind of the world that we're working towards to a degree. It's not about necessarily being like robot optimized as much as it is saying, these are the things you may care about. I may care about different things. How can we pursue our passions with vigor and have our bodies and minds feel great and perform great to that end?

Melanie Avalon
Okay, I love this so much for the HRV itself. And it's been a while since I had Aura on the show.

I had them on twice and it was a few years ago, but I remember diving really deep into how their technology measures HRV. And there are other devices out there that people have that measure HRV. I think like Fitbit and does Apple Watch do HRV too?

Jason Moore
There is some degree, I mean, I guess double clicking real quick. HRV is an umbrella metric or it's an umbrella term rather, for a whole host of other metrics that are basically like statistical analysis on your beat to beat intervals, those times between your heartbeats.

And so when people say HRV today, most of the time they're talking about this one specific metric called RMSSD and root mean square of successive differences, and that is what Auroring uses. That's also what's in your WOOP, if you have one of those, and then what we use in a lot of our metrics and readiness and recovery scores and things like that. So if you're looking at it through that lens, then no, Apple Watch doesn't use that specific metric, but they have another one, which is a bit simpler for HRV. And that one is a little less useful on a day to day basis, but it does have some utility, for example, if it's super low, then there may be some cause for concern, for example, but day to day, week to week, it doesn't provide the same decision making abilities.

Melanie Avalon
Oh wow, my mind is being blown. I did not know HRV was actually more of an umbrella for it. So you said it's like an aura, it's measuring what? What's it called?

Jason Moore
RMSSD, Root Mean Square of Successive Differences. And it's a mouthful, but it's actually, you can calculate it in Excel even. So it's not that crazy of a calculation.

The biggest challenge with these devices, the statistics are easy to calculate. But the hard part is getting a quality signal out of small, cheap, energy efficient sensors. And making it more convenient, for example, putting it on your finger versus having to wear like a chest strap. And so the gold standard for consumers is to get a chest strap for measuring HRV. And that's still recommended in 2025 if you really want to go down the HRV rabbit hole. But since we're kind of learned at a population level which metrics help with which types of decisions, we've been able to make it so that wearables with less accuracy and reliability can still be very useful in a day-to-day basis by measuring it from your finger, for example. Which is what our camera tech does and what wearables like Ora Ring do.

Melanie Avalon
Yeah, so the technology that you and remind me so for your timeline, because we talked earlier about the like the AI technology and all of that and data analysis, how did that line up with creating actual tech to do the actual measuring like in the from your phone?

Jason Moore
Yeah. So our very early innovations were basically we would take chest straps and we would use Bluetooth, which was new at the time to connect those to your phone and do HRV analysis on your phone. And that was really our first product and we put it out there. Pro sports teams and research labs just gobbled it up and that kind of catapulted our journey into this whole tracking space.

So basically our path evolved along two themes. One is people are like, oh, I love these insights, but I wish I didn't have to put on a chest strap and even professional sports teams with tons of money on the line with performance were like, you know, putting on a chest strap really just kind of annoying. And so we innovated towards making sensing easier and we made our own essentially like a pulse oximeter, which was hardware that you clip to the end of your finger to measure accurate HRV with. And that was one of our first innovations towards making sensing easier. And then in parallel, the other theme is, wow, so much new data about my body. What does this all mean and what do I do? Right. So it evolved quickly from just sensing to then guiding people towards the right information that they needed more the right products or services or, you know, other things that they needed to actually improve.

And again, that would be everyday people, even pro sports teams and top, you know, government, military organizations, like trying to figure out how to translate the data into action. And so the two evolution passed in there on the sensing side. We went from making our own physical, basically medical grade device to realizing that the camera of your phone is actually a very powerful sensor. And with the right algorithms and the right data behind it, we can get really accurate readings of heart rate, HRV, respiration rate and a full body composition analysis now using literally just the phone that you have in your pocket or on your desk. So that we can get into deeply. And then on the education side, it went from us teaching courses, which was really fun and exciting and educational for us as well, to building more automated guidance into our systems and partnering with coaches and gyms and health and wellness providers and biohackers and things like that to fill in content, products and services that could actually move the needle in people's data. And so we're just trying to make it as easy as possible for people to figure out what works for them, what is the data that they need to be tracking and what does it mean, and then connecting them with the, you know, again, product services and information that they need to do to make those changes. And so that's the timeline there has been basically the last 12 years evolving through those phases.

And we've been fortunate to serve over a million people with the platform and dozens and dozens of sports teams. And now, like, I think it's like 130 universities and research labs and we just soak up all this information and keep trying to knock down barriers of cost and access.

Melanie Avalon
Wow, okay, this is incredible. I definitely want to dive deeper into the actual tech because I know myself and a lot of questions that I get from listeners has to do with accuracy of these different scans and the data that's created.

So two part question there, so you mentioned that you can use the camera on your phone to both get this HRV type information as well as the DEXA scan information, which is fascinating and I'm really excited to talk about that. So my two questions are, one, can you talk a little bit more about the accuracy of these scans? And then two, what is the role of, so even, and maybe this isn't applicable, but even if it wasn't completely accurate, what is the, as long as you're testing within the same system, so this is more like a conceptual question, can you see changes because you're testing in the same system, even if it's slightly off? I know we talk about that a lot with continuous glucose monitors, like even if the monitor is off, you can still see the relative changes. Yeah, so two questions there, the accuracy, and then I know there's a word for this.

Jason Moore
Liability and consistency. Yeah, it's our precision as well.

Melanie Avalon
There it is, it's a P word.

Jason Moore
Yes. So yeah, great questions. And these are basically the foundations of the whole story, right? Is you need a certain level of accuracy and you need a certain level of precision.

The good news is kind of across, well, first I'll answer about us and then I'll just tell you kind of how I see the patterns across the industry. So for us, we start with accuracy as the like number one goal. Can we make this more accessible without sacrificing any accuracy? But if we do, how little can we make that, right? Like, can we make it as comparable as possible? So because we've kind of already come from the side of really being strict with the type of hardware that we use, like chest straps and our own medical grade device in the past, we had this really high volume of validated gold standard data coming through our system. So we're able to actually benchmark and have R and D volunteers help us compare the performance of our camera-based algorithms against these kind of validated devices. And then we also do a lot of independent studies with these labs. But for heart rate, we're essentially 99% comparable to ECG. For HRV, we're 97% comparable. For respiration, we're 99% comparable. For body composition, it's a little bit more of a complex suite of measurements, but the mean absolute error is 2.6%. And what that means, another way to say it too, is that we have a 0.95 correlation to DEXA. And that's extremely high correlation. The study, the most recent study that we've done was in partnership with the Pennington Biomedical Research Lab at LSU. And they're basically the top researchers in body composition are in that lab. And they compared three different DEXA machines side by side with Spren. And we were within the margin of error of the three DEXA machines were to each other. And so that's basically as good as you can get unless you go down the path of like autopsy or MRI, which are both. Autopsy is obviously a one time deal. So you don't want to measure your body composition that way. And MRI is cost prohibitive and out of reach for a lot of people, although that is getting better. So I will say that's exciting for the future is that MRI for a number of reasons is getting more accessible. In any case, that's kind of where we stand on the landscape.

And then from a reliability standpoint, this is the part that bridges nicely into what's going on across the whole industry. Our reliability reading to reading is essentially one to one. It's almost like there's no, there's a barely an error rate at all. And that is with an asterisk, because if you were to measure your HRV and then do a bunch of jumping jacks and then measure it again, you would get very different results. And so the reliability depends upon that you're doing the measurement kind of in the same way each time. And there's a tolerance level around what the same means. So for example, on HRV and heart rate and respiration, most of the time people do it first thing in the morning when they wake up, and they'll just either use the restroom or just do it straight away in their bed.

Jason Moore
And that is plenty of repeatability. You don't really have to overthink it beyond that.

For HRV specifically, if you do it lying down or sitting up, you want to do it the same way. So don't lie down one day, stand up the next day. But other than that, you can plus or minus an hour or a couple of hours even is not a big deal if you wake up at different times on different days. Although from a biohacking and longevity perspective, that's a different conversation. And then body composition very similar is ideally you can just do it in the morning, which your phone allows you to do. And kind of like blood labs in a way, DEXA scans are... DEXAs are amazing machines, but if you go schedule a DEXA and you go get it done, there are a lot of confounding variables in that data if it's at a random time of the day with a random level of hydration. And depending on what you ate over the last even 48 hours, your scan could be meaningfully different depending on the ranges that you're looking for. And so this leads all the way to kind of this pattern that you see where consumer tracking products actually end up most of the time being more reliable than their lab counterparts unless there's like a person in the lab controlling all of those variables. Like if you're a part of a scientific study, for example. And the reason why is because most people's lives are pretty routine and you can work these measurements in a routine way into your life. And then the other is that the software actually can detect changes over time and correct for it. And so that's some of our secret sauce and same for some of the other wearable and tracking companies. Their secret sauce is looking at, okay, if you do a body composition, in our case, which is a more unique tech, but if you're doing a body comp analysis once a week, we can kind of isolate out changes in your water weight over time. And then it doesn't matter so much if you're over hydrated or under hydrated for the scans because we can see that variable and isolate it out. And that ends up making it more reliable for the underlying analysis than if you went and got a DEXA scan once a quarter, let's say. So that's exciting.

It's pretty much all data sensing technologies are going in that direction. We as well, obviously. So you got to start with that foundation of accuracy, and then also layer in that reliability and repeatability or precision, as we said.

Melanie Avalon
Oh my goodness. Okay. So many things here. And I will say the doing the, the body composition analysis scan was so cool. And I have so many questions and thoughts.

I was actually going to ask because you were talking about its comparability to DEXA, which I've done a DEXA scan a few times as well. I was going to ask, and I think you answered it by saying it was within the margin error that DEXA has, because I was thinking, I know people say that DEXA isn't always, you know, completely accurate. So it's like, how do you even have a control? Like, how do you even, how can you ever have a completely accurate control? Cause you just won't know. Right? Like you don't actually know the right answer, the true answer.

Jason Moore
Exactly. And that's why I made the joke about autopsy earlier, right? It's obviously not practical for most use cases, but it is basically underneath this is there's a broader conversation, which I also, anyone that hears me do this, make this mistake, please just message me because I'm trying to be more precise with my own language. But there's a difference between measuring and estimating almost all the metrics that we all use today are estimates, not measurements.

So a measurement is like, you know, one inch or one centimeter, or if I, you know, if you do an autopsy and you cut all the fat out from a body and then you put it on a scale, you know exactly how many pounds of fat there are, right? Everything that is not a measurement is pretty much an estimate for practical purposes. And so then you're trying to say, okay, well, how close is my estimate to reality? And also from a practical perspective, does estimating make this data point just so much more practical, which obviously, if you're comparing against autopsy, is a pretty obvious change in practicality. But from a DEXA perspective, if you're, this is a conversation that let's say bodybuilders often use DEXA for like year round analysis, but then if they're prepping for a show and they have this really, you know, each percentage or half a percentage of fat or things like that matters greatly, they just stop using the measurement tools completely. And they just start using their eyes or the trained eyes of their, you know, coach to see if there's changes happening, because the margin of error on DEXA isn't granular enough for that use case to really dial that level of detail in.

Most people though don't need that level of granularity in their body composition analysis. And even if you're optimizing longevity or performance, that level of granularity is there's not really any data supporting that it's beneficial to get that deep. So DEXA is considered the gold standard for all intents and purposes, other than really dramatic changes in your hydration. DEXA can be thought of as a very accurate and reliable estimation of body composition.

And then, you know, peeling back from there, like tools like ours, for example, increase the precision because of the repeatability and the frequency go up. And then also, and you can control variables a little bit better that way, but then also makes it far more practical, because as I'm measuring a little bit more frequently, and this is some stuff that again, we learn from our members and our customers as well, we don't just know all of these things, but as people measure it more frequently, they can actually see changes in hydration as well, which is not something you would use a DEXA for. And people are starting to see that if they do their body comp analysis and their water is changing and their weight on the scale is changing because of water, that one, that could be motivating or helpful if they're trying to lose fat or build muscle,

Jason Moore
but it also can be helpful to know how well they might perform that day or whether or not they need to focus on hydration that day. And so you would just never get that level of practicality out of a DEXA machine, even if it is very useful for other things.

For one caveat real quick is that we don't offer bone mineral density. So there may be a segment of the audience out there that's like, Oh, my doctor told me to get DEXA for bone mineral density. Can I just use Spren for that? No, we can't see inside the body and we haven't yet body composition side. Yes.

Melanie Avalon
And I will say for listeners, because I think, well, A, I feel like people often get their, like their wearable device, and then that's their device, you know? So they're like a whoop person or they're an aura person.

And so people might, if they hear this and they hear that it's HRV, they might think like, oh, well, I already have, you know, whatever that measures that. Like the body composition scan, oh my goodness, friend. So I did it. So I've done, I did it twice. And actually, I have questions about that. I did it back to back. It gives you, you get this report and I have it in front of me right now. So you get your, your overall body composition analysis, your body fat percentage, a body composition chart, a fat distribution pattern, an Android gynoid ratio, body mass index, lean mass index, fat mass index, resting metabolic rate, which a calculation of basically the calories that you, you know, burn daily just from your resting metabolic rate, it is so cool.

And there's like charts and all the things. So this is, you know, way more if you're hearing this and thinking, you know, oh, I already have an orangue for HRV. There's a lot here that's not in your orangue. So some, some questions here. So like I said, I did it. I was really curious. Well, first of all, I'm just blown away that it can calculate all this from the pictures and the way it works, at least right now, has the picture taking process evolved?

Jason Moore
We are always updating those things, but yeah, I mean, basically, it's kind of like if someone has deposited a check with their phone, you know, like you, it automatically detects when you're in the right position and detects lighting. This is another way we can increase precision and reliability is we in real time, we can detect the changing conditions in your home if you're doing measurements in your home and say, Oh, the lighting is a little brighter today, or you're standing a little further away from the camera today, you know, that type of stuff, and we can control for all that.

But then it just takes the snaps a photo front and side. And, you know, we don't store photos of people. And that's a question we get often about privacy, we can get into that if you want. But in any case, it takes those photos automatically when you're standing in the right position.

Melanie Avalon
Yeah, I was blown away that it could get all this information from those two pictures. I was curious why, especially after hearing what you said about how it learns over time with your pictures, why would it not have you take like three pictures at the same time just to average them together or look for differences?

Jason Moore
Yeah, it's a good question. So we do take the two, the front and the side view.

And what's interesting is the picture taking part is actually, you know, thankfully we're kind of writing the coattails of companies like Apple and Google and Samsung and stuff who have developed these amazing cameras. And the picture quality is not the limiting factor at all in this analysis.

Melanie Avalon
That was one of my questions.

Jason Moore
Yeah, so thankfully pretty much everybody with a modern smartphone has a powerful enough camera in it. And really what's most important is, is there adequate lighting? And are you wearing the right clothing, right? So we recommend either like skin tight workout clothes or underwear or something like that. Again, it's all private.

So your images are deleted as soon as they're processed. And you can opt to save them on your own phone if you want, or you can opt in for certain R&D programs, but those are definitely optional. And so, but in any case, the phone or the picture, taking multiple pictures is actually we found unnecessary. And you'd be surprised also, maybe not, but I kind of get surprised sometimes by how quickly the consumer expectations change. And so taking multiple photos actually significantly, it adds enough friction to where people are like, I just won't do it today.

Melanie Avalon
Yeah, I thought that I thought that was the primary reason actually.

Jason Moore
So first of all, we try to educate people, and there are certain things that we're kind of, some consumers think it's annoying, but we're like, hey, no, you can't use that device because that gives you trash data. And they're like, but come on, I just want, and we're like, well, there's a line somewhere, right? So we try to accommodate as much as we can for, we call ourselves device agnostic. So do whatever phone you have, or whatever wearable you have, depending on what you're trying to track, we try to work with it, but we do have, you know, boundaries.

And so, but then yes, we found that that wasn't necessary for accuracy and precision. So we're like, well, more accurate and more precision is always better independent of other variables, but it got in the way of compliance and consistency. So we ended up reducing it to one. And that is actually what we use for the validation studies. So our validation studies comparing us to Dexas with a single image. And yeah, so it's highly accurate still.

Melanie Avalon
Wow. Okay. So how often should people do this scan?

Jason Moore
For body composition, we typically recommend once a week and have found that to be really a good balance of frequency and useful. So you can do it less frequent too. I mean, once a month is great also, if that's what you prefer. It's hard for people to build a habit on that type of cadence though.

Some people do DEXA scans like once a quarter, for example, and you can definitely still do it that way if you want on spren. But because it doesn't cost anything to do more scans, you can do them as often as you like. And some people do them daily. And we just kind of caution people to know that your body composition really doesn't change dramatically on a daily basis. The one thing that it does kind of pull out more is changes in water. And that is pretty cool. And we're working on ways to highlight that more automatically for people. But I will just say too that your scale in your bathroom also can help you learn more about changes in water because really day-to-day changes in your body weight are mostly water driven and that it takes time for fat and muscle to actually change. And hopefully your weight isn't changing due to changes in bones either, at least not in a noticeable way in any acute timeline. So once a week for the body composition. And we pair that in with our whole coaching platform as well. So we have all of this guidance and accountability and interpretation things that help you. And so if you do that, check in on a weekly basis, it'll also automatically cascade into changes in your nutrition plan and changes in your, maybe your exercise plan and other things based on changes in your body on a weekly basis. So weekly for the body comp, pretty much daily for the HRV and heart rate and respiration.

So if we want to double click on that for a second, we actually do integrate with pretty much all major wearables and trackers. So you don't have to use our camera tech for HR, heart rate, and HRV. If you don't want, you can just pull the data from your oral ring into the platform. And it's great if you like that device and it works well for you. We're happy to use it. And so other wearables also, of course, but in any case, looking at that daily first thing in the morning is where people get the most value out of it.

And you can also miss days and it's not a big deal. So with HRV, we establish this baseline over the course of your first week and then continuously beyond that. And you kind of need to do it like four days a week to really maintain that baseline more is better. So we just tell people do it every day. And if you miss days, then it doesn't matter too much.

Melanie Avalon
So I'm underweight just like from a number perspective. So if you're underweight, is it possible to get... Does that mean that automatically your muscle is going to be under as well and your fat is going to be under?

Or what I'm trying to like articulate or ask is if it's a ratio of muscle to fat, could you have an okay ratio but you're underweight so it's never going to say that it's adequate muscle?

Jason Moore
So there's probably some overlap between those, but I think the short answer is no with some nuance. And basically what I mean by that is, if you're really light with a thin frame and things like that, your body weight is just going to be lower than other people who are your height.

And the BMI benchmarks are kind of off of averages and norms. And so I'm also quite light and I default to being lighter than heavier. And one of the biggest aha moments for me personally was always kind of thinking of myself as relatively fit, is that over the course of my 20s and into my 30s and now on, my lean mass was deteriorating, but my weight was staying the same. And so outwardly, I kind of looked the same basically, especially in clothes, but over the past two years of developing this body comp tech and just becoming way more acutely aware of what my body composition was doing, my body weight is actually the same, but I've been able to cut half of my body fat out and gain 15 pounds of lean mass.

Melanie Avalon
Oh, wow.

Jason Moore
Yeah. And so it's been, you know, I had a base to build from a fitness historically.

So that type of transformation may or may not be accessible on that same timeline to everyone, but just measuring it and seeing the difference between my lean mass and my fat mass independent of my weight was the thing that kind of unlocked the ability for me to do that, or at least be aware of what I needed to do to do that.

Melanie Avalon
Wow, yeah, that's amazing. Yeah, it definitely made me rethink because like at the beginning, it asks you what your what your goal is, like lose weight, or sorry, lose fat, gain muscle maintenance. So I think I've done maintenance.

But then when I got my results, I was like, Oh, maybe I need to do gain muscle. That's my goal.

Jason Moore
Yeah. And there's, you know, there's, there is nuance even to that, right? Because I will say that our algorithm right now around muscle building and fat loss, it tends to lean towards longevity. So because the average person cares a little bit more about how they feel and about their health than they do about, you know, a specific performance metric.

So if you were like a hardcore athlete and you wanted to build muscle, you might intentionally overeat a lot and just not care about the cascade of potential health effects in the name of performance. But since our system is designed more for every people, every people, and basically, if you select muscle building, it's not going to turn you into a monster. It's going to help you build healthy lean mass while maintaining your fat or even potentially decreasing it in a re-composition, depending on your experience level with, you know, different nutrition and exercise modalities.

Melanie Avalon
I do say I have a request sort of because you pick like what diet you want and it's balanced or low carb or low fat I think were the options and actually this is a question for you there like for me I actually do I on any given day I'll do I don't like combining high carbon high fat so I will do either a low carb day or a low fat day I don't really like combine but I also don't really stay on one indefinitely so what would I what would I pick there if I want to go back and forth.

Jason Moore
It's a good question. I would pick balanced and, and basically I would then just, uh, within those, you can also change the, um, percentages between like carbs and fat if you want, but really for body composition, if you're just purely think about body composition, the balance between carbs and fat often is more of a matter of individual taste or individual preference.

And maybe baked into that is also what works best for your body. And where I'm going with that is basically the two big factors for body composition is adequate protein and then also total calories. And so you want enough total calories, but not too much and enough protein. And most people don't get too much protein. So you don't need to worry about over eating protein. I might. And to be fair, I might also fit into that camp sometimes too.

Melanie Avalon
Literally, this question haunts me. I eat so much protein. It's shocking. And it's all like whole foods protein. Like it's just eight like pounds every night of meat, seafood.

Jason Moore
Well, hey, so this is unsolicited, diving into your personal life on that, is if you are feeling great, if you're sleeping well and you're otherwise healthy so that your kidneys and your liver and your digestive system can process all of that, then there's really not a lot of evidence of a downside of doing that. The main downside potentially is cost because protein just costs more than carbs and fat on a dollar per calorie basis.

And then the other is, depending on how literal we're taking the scenario, if you were just only eating steak all the time, for example, then you would maybe be risking nutrient deficiency or insufficiency just by not having enough variety. So if sleep's good, energy's good, digestion's good, there's really not a lot of downside to doing that, and your other health markers are in check as well.

Melanie Avalon
Yeah, it was, it was funny because I was in the app and it was saying the excess protein started at 140. And I was like, Oh, I am definitely over that.

Oh, man, I would be starving if I just ate that. Actually, another really quick question about about taking the picture, because I thought about this after doing it. What is the role of if you're flexing or not? Does that affect it?

Jason Moore
Yeah, so you want to relax. And that being said, if you flexed every single time, it would probably be fine. A precision thing. Yep, precision for decisions over time. But I think it's better to stay relaxed.

I mean, from the accuracy, pure accuracy point of view, it's better to stay relaxed. But also, I think practically, it's better. And then one of the things that we're adding in relation to that question is the ability to take separate progress photos. And so people in the picture, I'll just say like disclaimer to everyone here is that to get the consistency and the accuracy, we have you put your phone on the floor. And that means you can do it almost anywhere. Most people just do it at home in the same spot each time. But the downside of putting it on the floor is that the picture is just not the most flattering.

Melanie Avalon
Yes, I was thinking that I was like, Oh,

Jason Moore
Yeah, so I'll just be real about that and say that if you're doing progress photos, then we kind of just want to make that a separate or you could pick your phone up and put it maybe like waist or hip height or chest height, something that's a little bit more flattering. And then you could flex or do whatever you want for that. And then you can see a little bit more of that progress in the way you want to. But you can see visual progress.

I save all of my scans onto my phone and then I have to hide them in my iPhone photos because I just have all these pictures of myself and my underwear in my iPhone photos and because I'm testing this thing all the time. So then I have young kids and then they get into my phone and I'm like, I don't need those photos going places I didn't expect. So I use the little hide function in iOS that puts them away. But in any case, yeah, the progress photos I just take separately for now and we're going to build something into the system to make that easier for you to do directly if you want to.

Melanie Avalon
Also another thing that a little side benefit that people might get if they're taking the scan regularly is it definitely made me much more aware of my posture by taking the side photo. I was like, oh, this is something I need to work on.

Jason Moore
At the end of the day, really, I think for most people, these things are awareness tools, exactly what you just said. You may not want to measure all of these metrics every day or every week for the rest of your life and I would completely understand if that was your stance.

As a platform and as part of our mission of being device agnostic and trying to support all the different things that you might be trying to achieve, not boiling the ocean but one step at a time. Anyways, the goal is to make it so that you also can feel and understand the feeling of changes in your body so that you can react even quicker. The ideal is to get real-time feedback and swinging back to HRV on that, that's where breath comes in as a biofeedback tool. People are not always aware of their posture, their breathing, how they're holding their spine and things like that, that impacts your focus, your energy, and then your structural health over time tremendously. And there's just little things that you can do to chart a much more positive course.

Melanie Avalon
Yeah, no, this is incredible. Actually, I have one more question about the scanning process.

At the beginning, it says there's like an athlete mode for low body fat. Is that for just athletes or is it for people like for me where I'm lower body fat?

Jason Moore
There are some kind of genetic, some people need to check that on for genetic outlier-ness, right? And technical term, outlier-ness. And, but most of the time that's for actual athletes and usually it's because they have a history like of extensive like strength training, for example, that causes a really high degree of muscle density. And sometimes athletes can look soft on the outside but actually have a ton of muscle. And so that just helps flag for the system to be extra aware of that. It's not actually completely necessary for most people still, even athletes, but it does help in some cases.

But yeah, there might be, you know, again, relating it back to the heart rate side. Like I have a genetically low heart rate. My resting heart rate is like 44 on average and I'm, you know, decently fit, but I'm not like a ultra endurance athlete or something. And so these are just genetic variations that everyone experiences. And so including on body composition, that might be the case.

Melanie Avalon
Gotcha. Would you ever integrate with people putting in their genetic data?

Jason Moore
Short answer is yes. I mean, basically, there's any data that you might track. We are interested in including and it's just more a matter of how much time and resources we can put towards any given one.

We're in the realm of epigenetics because we're looking at how changes in your physiology manifest over time. That's maybe a simplified relation to epigenetics, but genetics is really your starting point, your raw material. It's not something that you can easily change, but it gives you some insight into why certain things might be harder or easier for you. That's important information.

Melanie Avalon
Awesome. And, and speaking with you kind of, you know, mentioned or touched on it preferably right now with, you know, the time and resources to for all the things you're doing. So you guys raised 11.3 million in seed money from investors, including Eli Manning, which is super cool.

Did you personally lead the fundraising campaign? And what was that like, just the experience of going out and, and raising money and, yeah, the response.

Jason Moore
It was a very good test of my heart rate variability and yes, I did lead it. I was extremely bad at it early on and I've gotten better at it over iterations and experience, but you know, to add a little fun color to the story is we raised our first round. My co-founder is actually my wife and she stays behind the scenes a little bit. She's 10 times smarter than I am at basically everything, but we were either pregnant or had her first baby right around the first fundraise and if I remember the timing correctly and then went on to have another side about two littles running a high growth tech startup that's venture backed and raising funding and, you know, having millions of users and stuff while being married to your co-founder and having kids is a very challenging group of things to try to do.

And I for sure saw changes in my data. I can see the births of each of my children in my data and I can also see exactly when we did fundraising in my data. It's stressful, but it's kind of part of my high performance passion pursuit. And I actually, a lot of people, especially entrepreneurs and nerds like myself talk about how they hate fundraising and things like that. And I could totally see why because it's a huge time suck and you most of the time investors or potential investors are just telling you that you're, oh, you seem very smart, but you're kind of actually dumb because you're missing all of these things and you, you're going to fail and we're not going to give you money. Most of the time that's the type, you know, it's not quite so direct and blunt like that, but that's kind of the sentiment, but I actually found those to be extremely educational moments and, um, getting better at fundraising.

I asked, I had to be careful to not only get better at the fundraising part, but to also learn how to translate that advice into the business. And some of the advice was terrible and others were, was game changing. And so we received advice from investors who told us, no, that completely changed our outlook on some of our business model and what we were investing our money in and stuff like that. So I'm super grateful for all of those, even if there was a lot of stress involved in it, our current investors are awesome. And, you know, I would say that behind closed doors too, I don't agree with them on everything and they don't agree with me on everything. And that's also beautiful in its own way, but they challenge us, they push us and they also have supported us when others didn't. And so been really fun to learn from all that and kind of surreal in a way too. Cause again, I don't, I don't necessarily come from money, but when you start getting wired really big checks, you realize, Oh yeah, there's really smart people who believe in me and I have a responsibility to, you know, deliver things that they're looking for as well.

Melanie Avalon
Amazing. Yeah, part of my question I'm selfishly asking because I'm about to start fundraising for a project and I've never done it before and I'm just like, so yeah, that's incredible though.

Hopefully my background in acting and auditions and being used to rejection will.

Jason Moore
Oh, you're going to be like light years ahead of where I started because this in the end, you know, there's like two big components of this of all of these business ventures is that like how differentiated is your value proposition, right? And then also how well can you get people interested in you, right?

Like in a sense, distribution and attention and things like that. And usually businesses have like one or the other, but not both. We were heavy on tech and innovation and light on distribution and marketing and, you know, things like that. We kind of had to learn how to get better at that over time.

Melanie Avalon
Okay, I'm just being selfish now. Did you find anything game changing in that for the attracting users?

Jason Moore
Yeah, I mean, well, I mean, definitely one is kind of the fundamentals of solving a really burning problem for them, right? So that's one thing that we've always been fortunate is that our tech is usually quite unique and you can't really find alternatives to it very easily. And it solves a problem in the sense that lots of people want to learn more about their body and measure these things, but it's either expensive or inconvenient or hard to interpret all of these types of things. So over and over again, we're solving that problem and that really helped having those strong foundation to build on.

But then trying to find the right balance of saying like, here's how cool it is and what it can do, but not saying it can cure cancer, right? Or something like that and finding the right balance between hyping people up and not overpromising the world really kind of pushes you towards overpromising and because there's just so much noise in marketing and media and stuff like that. But time and time again, we have found it is better to underpromise and overdeliver. It's really hard to do. It's really hard to do. With some practice, you can get good at that. And that changes the conversation with investors, with customers, with everybody, basically.

Melanie Avalon
I love that idea, especially with under promise over deliver, because at the very least, then hopefully you come out even, you know, like you don't under deliver because you under delivered you under promised. So really, you can only hopefully win with that approach.

Yeah, exactly. Were there, I'm curious, were there any aspects of launching and the tech and what you were marketing to users that either A, you thought users would be more interested in and they weren't. And then on the flip side, things users wanted that you and were interested in that you didn't expect them wanting.

Jason Moore
Oh, for sure. Yeah, definitely. I mean, we've I've had plenty of moments in my team and my wife and everybody would would chuckle at I'm like an idea machine and probably 90% of my ideas are terrible. The good news is, is that I've learned to kind of figure out which ones those are with practice.

But we've built things that we were like, this is going to change everything. And then no one cared about it. And actually, along the way, everyone said that's going to be so cool. A really ridiculous example is that in the very, very, very early days when we had like few hundred active users.

Melanie Avalon
When were those early days, by the way?

Jason Moore
So this was over 10 years ago. This was the app, our original app, Elite HRV, launched in 2014. And we started the research on that about a year before and, uh, for, for the specific app. And then I was already kind of looking into this whole tracking space in like 2011, 2012.

And so that was sort of the genesis, a lot of these ideas and, and realizations, but with a few hundred users, we were like, we're going to build a crowd sourced language translation dashboard that allows our users to translate our app into other languages. And it sounded so cool because we were getting all of these people in all these different countries picking up our product and they were asking for that. They were like, yeah, I just really need, you know, this language or whatever. And we even had one user translate our whole app into Finnish and Portuguese cause they happen to be fluent in those two languages. And then we just got tons of complaints from other languages that say, why do you only support Finnish in Portuguese and not our language here?

Melanie Avalon
Oh man, then you made other people upset.

Jason Moore
Yeah. And so, and then actually what we found in reality is that for the first, I mean, even today, really, probably continuously, most of our adopters are able to read things and in English. And so they want it in their native language. And we also would love to support that.

But what we have found is that every time we've made an effort in that direction, it hasn't really led to any changes in usage. And the good news is that AI is going to solve that anyways, because now our AI coaches in 36 languages and the app itself will be shortly behind it. But in any case, that's an example of like, listening to people who are really wanting stuff. And as a new venture, we were so excited by all this attention. And we would build things and then basically no one cared. And we were like, okay, so if the customer isn't always right, then, you know, how do we figure out what to build?

And we kind of learned that sweet spot between listening to customers, but not to what they say that you should build, and more figuring out what their problems are. And which of those problems are going to be underserved in the market and high value so that that people are willing to pay for them. And then in line with a vision that you might have of where the world is going. Like for example, we have this underlying belief that making sensing like high quality sensing of the body, more real time, cheaper, more passive, is just always going to drive progress in a way that's meaningful. So we're always trying to make our sensing tech easier, cheaper, you know, that type of thing.

But anyways, yeah, that's stuff because you want something that just the world wants to pull it out of you, but then pairing it with a financial model that makes sense and a distribution model that's scalable and all that type of stuff is another problem to solve.

Melanie Avalon
Yeah, I'm so fascinated by all this. One last question about it because I actually have an app that I created, but it's super, super simple. It's simple. It's for looking at different problematic compounds in foods, like 11 different compounds, and so people can find what they're reacting to.

And then the project I'm working on right now is a dating app. But Android versus Apple users, have you seen, is there a ratio difference there? And does it match the normal? I'm curious if like health and fitness people are, if they are the norm for the Apple versus Android debate.

Jason Moore
Yeah, it depends a little on geography, but by and large, people who are more into tracking and into biohacking and things are iOS. And the percentages, again, kind of depending on geography and like segment and stuff, it can be quite high actually.

It's like in higher end biohacking circles, it would be like 90 to 95% iOS. But if you went to like an average YMCA or something like that into a gym, it'd be closer to 6040 or 5050 in that environment.

Melanie Avalon
Oh, wow. Okay. And then speaking of the future, so I feel like everything is so rapidly advancing. It's wild.

Like it's just crazy with AI and technology and everything. So what do you see on the future horizon, I guess in particular for your company and everything that you're doing, any exciting future tests or things that it will be able to test that we can't test now, like the bone density or yeah, just in general and with the AI evolving, just what do you see? What do you dream about?

Jason Moore
Yeah, well careful what I dream about it cuz I can go way off into the weeds on too many dreams But the not literally I guess but in any case there's gonna be a lot more that we can sense And so we have a pretty clear path to things like blood pressure Things like cardio respiratory fitness or vo2 max estimations using just your phone also and There's other markers of longevity and performance such as strength mobility balance you know movement mechanics and things like that HRV is kind of a proxy measure into inflammation which is unlocks this whole other category of things that people would be wrestling with but there are certain companies that we have some partnerships with and we may innovate on in the future that are starting to be able to Detect blood markers using non-invasive sensors and so that's exciting an exciting path of research now that's gonna collide with some of these other aspects of the industry like AI like you mentioned and so as we kind of inundate ourselves with more and more data the systems for gathering interpreting and Translating that data are becoming easier and easier and more and more powerful And so there was kind of there's always this like rollercoaster of saying like oh track more because then you can learn more about yourself but then it adds stress of in and of itself and you're like I don't know what I should supposed to be paying attention to and what should I be tracking like you said at the beginning and AI in some ways is going to make that a lot more practical especially as tracking becomes more passive so wearable one really cool thing about wearables is you just put it on right and then you don't have to think about it after that too much and The trade-offs and accuracy and precision or battery life or all this stuff is You know superseded by the fact that you can just put it on and then you don't have to think So that's great And I think more and more tracking is going to go in that direction and and then the interpretation of it This is where you can kind of get really excited if you're like a Star Trek II kind of person

Melanie Avalon
Like the tricorder thing.

Jason Moore
Yeah, like a tricorder exactly. And also connecting these systems together to where like let's say you're sleeping and I don't want to give away all my cool ideas. No, I'm just kidding. But let's say you're sleeping and I'm sure the folks at Aura and Ultrahuman and companies like that are already thinking this. It could connect your sleep data to your thermostat and so it could change the temperature on your thermostat, even just a degree or two here and there, and then measure the impact of that and say like actually for you the optimal is 67 degrees Fahrenheit instead of 68 or whatever.

Maybe that's different if you just pounded two pounds of steak. And so these data points are all going to start to not only integrate together for you to make better decisions, but also with your environment where you mentioned your posture. For example, I have a sit-stand desk and I often forget to move it from to standing or to sitting. And right now I have now the ability for my Spren AI coach. I tell my Spren AI coach, hey, I'm trying to work on being better at sitting and standing and it'll actually text me proactively a couple times a day and say like, hey, have you changed the position of your desk?

And so I'm like, oh, thank you. I forgot. And so then I change it. That's really cool and it's a huge step forward. It's like having this shoulder angel that's there to help you with that. But even cooler to me would be as if my desk just knew when I was having a break in focus and then just changed my desk without asking me.

Melanie Avalon
Yes, that's what I was thinking like, or thinking like if I had, it'd be cool if there is an app on your phone that somehow knew if your posture was off and would tell you.

Jason Moore
Well, we have so yeah, and that's where some of our tech that we've innovated, it's just sitting on a shelf because we haven't had time and resources to deploy it in a way that, you know, we pride ourselves in the quality of the products and it's hard to just throw things out to the world, but we have a system that can detect heart rate, respiration, and HRV contactlessly from your face and using just like your webcam, for example, stuff like that. And so not only is that interesting because you could stream your vitals to let's say a telehealth provider or something, but also you could imagine products built where it's like checking on you every now and then to see if your stress levels are up and then maybe suggesting like a gentle breathing exercise or going for a quick walk if you've had a really sustained level of stress and you're starting to lose focus.

And some people get excited by that. Other people get freaked out by it. But to me, this is an inevitable path into the future and it's more a matter of, you know, how do we work with people that we trust and products that we trust as well as is this technology working for you or is it working against you some way in the background anyways? And so, you know, we're obviously, again, this is maybe another layer of the philosophical and political side of it, but AI and tech right now are great for productivity and also terrible for mental health and physical health.

And there are many billions of dollars are going into distracting you and pulling your attention away to things that don't matter. And I'm excited about, you know, again, with the support of our investors and our team and everybody involved channeling all of that power into your health and your longevity and your performance. So that's kind of what's exciting for me.

Melanie Avalon
So incredible. Yeah.

I, um, I feel like I, uh, you said you call yourself an optimist, right? Or did you give yourself a phrase? Yeah. Like when it comes to everything in general, I'm an optimist as a person, I'm an optimist when it comes to AI. I'm, I think I'm a cautious optimist. I don't know. I feel like it's either going to continue to be amazing or we're doomed. So, I won't be surprised if it goes south and I'm probably on the bad list because of the way I interact with chat GPT, but.

Jason Moore
and you tell it to F off and things like that.

Melanie Avalon
I cannot handle its hallucinations. I just can't. And then I get annoyed at myself. I'm like, Melanie, why are you arguing with this thing? But I hold it accountable. I will not let a guest light me.

Jason Moore
That's good, that's good. No, you got to stand up for it for yourself. And, um, you know, I think that's actually helpful to the system. I wouldn't say directly, uh, necessarily that it's set up to like, learn and be better in that exact moment, but we do need to steer these things and we need to, you know, stand up for truth and accuracy and things like that.

And then, uh, also, you know, to a degree, your, what you're describing also makes AI interesting for things like therapy or things like health coaching and stuff, because, you know, you can kind of, there's a social element. Like we're just so social creatures that I will go somewhere and I'll be at the grocery store and I may change my behavior slightly based on who's walking down the aisle in the grocery store. Right. And it's like, why would I even, why would that person even be on my radar at all? I mean, never see them again. They probably don't matter at all to me in my life. You know, most of the time it's just that I like smile and wave at people or something like that. So it's not a big deal, but that level of like social influence that we have as humans, there's a little bit of relief when it comes to chatting with AI.

And that's something that research is starting to show as well. Maybe you just need a vent until, you know, you can tell the AI, like screw off, you're the worst. Uh, I just need to get this off my chest. And it's amazing at bringing that conversation back around and saying like, you know what, I am the worst. You're right. I suck.

Melanie Avalon
That just makes me more upset, though, because because it'll be like, you're right, I did that. And I'm like, OK, OK.

So like and then it'll be like, it'll be like, I'm not going to do that again. Like, yes, you are. Like, don't tell me, don't make promises. And then it promised not to make promises. And I was like, you just promise not to make promises. Stop. I cannot.

Jason Moore
There's a lot of work to be done there. That's, you know, earlier you asked me about surprises and like gotchas and stuff. Those are some of the things that, because again, our, our scope is narrow, uh, narrower that we try to basically eliminate all of those types of things. So we have layers to our AI where it's actually checking itself as well.

And so if it says like, if you're like, Hey, can you go to the store and like buy me some food, it'll be like, sure, no problem. You know, our, our AI won't do that because before, before it would promise to go do something in the real world that it can't actually do. We have a system that's checking for that in the background and it's not perfect. We have always room for improvement just like any company, but we feel very strongly that being in the health and performance space, we need to get as close to accuracy and precision on all things. And so, uh, that's a big one that we check for.

Melanie Avalon
Yeah, I've been thinking about a lot recently because I was telling you before we started recording that I'm working on an AI with another partner, but for my other podcast, basically to answer their questions about intermittent fasting and provide support and guidance. I'm just nervous because I got to make sure that it's accurately representing what I think.

So it's an interesting journey to be on, for sure.

Jason Moore
Totally, totally. Yeah, it's a major unlock and also a rightful source of stress for a lot of people.

Melanie Avalon
but so much, so much potential. Well, this was absolutely amazing. I'm so grateful for everything that you're creating and listeners, like we were talking about, there's the HRV part and then just this body composition scan is the coolest thing ever. You've got to try it.

Like go get the app right now and Jason is so kind. We do have a code for you, but quickly you will, like I said, you'll be able to actually get this data on your body fat, your lean body mass, that the ratios, your improvement over time. It is so easy to do, so cool. You're resting metabolic rate. I'm genuinely so impressed. And that's just one thing in the app. There's like we talked about in this conversation, there's an AI coach that helps you through everything. It helps you make changes and actually get achievable results that you are seeking. So you can download the Sprint app in the app store. That's S-P-R-E-N and Jason is so kind. You can get with the code Melanie Avalon, you will get a free trial and then also 50%, so five zero percent off your first month as well. So cannot recommend this enough. Go to the app store now, sprint and use the code Melanie Avalon. So thank you so much, Jason. Was there anything else you wanted to touch on or share about the work that you're doing or anything you want listeners to know?

Jason Moore
No, this is awesome, Melanie. Thank you, a great conversation. Obviously, you live and breathe this stuff. And that's very clear.

And yeah, I mean, we're discovering new stuff all the time. So I'll have more to talk about in the future. But I think we really hit on things pretty well of what we're up to right now. You know, body comp has been a hot topic for us lately. So thank you for highlighting that. And then, you know, translating that into the nutrition and the coaching and stuff. More recently, I guess one announcement is that we're partnering with gyms and health clubs and sort of like physical world businesses more now and helping our system help people in those environments. So that's kind of a really exciting chapter where pretty soon gyms near you will have spread in them.

Melanie Avalon
That's so cool. And so like realistically, what, what is that going to look like? Like the gym will like, how will it manifest in the gym?

Jason Moore
A lot of the stuff that we talked about today will still just apply in the sense that you can measure your body composition and nutrition just using your own phone, using the Sprint app, but beyond the data that you have about yourself, we are also partnering so that the AI and the guidance system knows what's in your gym and what's available to you there and what types of workouts you could do there or how to make the most use of your membership to improve your body composition or your longevity goals. And so we're starting to partner to bring other types of data in and to the system and make it even more kind of intuitive to translate what your data is telling you to what do I do when I go to the gym or how do I stay consistent or should I be focusing more on strength or cardio right now, that type of stuff.

So pretty fun with our partners and then the AI ends up being able to take on their personality too. So without going off into the weeds on that, different gyms have different vibes and different ways that they like to guide their members. And so we actually add an element of that into our AI experience as well so that the gym can kind of have a branded experience while you're there.

Melanie Avalon
Oh wow, super cool. Okay, well this was absolutely amazing. Thank you so much again.

The very last question that I ask every single guest on this show, and it's just because I'm very passionate about mindset, so what is something that you're grateful for?

Jason Moore
Oh, gosh, I have too many things, but the number one thing is my wife and kids. I'm not joking when I said earlier that my wife is 10 times smarter than me and she changed my life. I say I became an adult when we started going steady, as they say, once upon a time. And this company and my kids and my lifestyle that I have right now would not be possible without her and I joining forces. So I'll throw that shout out there for some brownie points too, but it is true.

Melanie Avalon
And I love it. Oh my goodness.

Well, thank you so so much, Jason. We'll have to have you back in the future assuming we'll stay optimistic assuming that we aren't doomed with AI, like a year or so, if we're still around. Thank you so much for everything that you're doing and we'll have to talk soon.

Jason Moore
Thanks, Melanie.

Melanie Avalon
Bye. Thank you so much for listening to the Melanie Avalon biohacking podcast.

For more information and resources, you can check out my book, What, When, When, as well as my supplement line, Avalon X. Please visit MelanieAvalon.com to learn more about today's guests and always feel free to contact me at contact at MelanieAvalon.com and always remember, you got this.