theCUBE + NYSE Wired: MedTech Unplugged, the Future of AI in Healthcare & Life Sciences | Eric Litman, Aescape

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Eric Litman

CEO

Aescape

Inside the MedTech revolution: 5 ways AI and robotics are redefining care delivery

Patient-centric care is no longer a future goal; it’s the foundation of today’s most groundbreaking medical innovations. From artificial intelligence-driven diagnostics to brain-computer interfaces and robotic precision in fertility and massage therapies, technology is accelerating personalized treatment in ways that once seemed unimaginable.During conversations at theCUBE’s New York Stock Exchange studio, theCUBE Research’s John Furrier and Dave Vellante sat down with MedTech leaders who are rethinking how care is delivered. Their conversations revealed a shared vision: using automation, AI and smart design to make healthcare more precise, accessible and truly centered on the patient

play_circle_outline Eric Litman's motivation for founding Aescape based on personal health experiences.

play_circle_outline Description of Aescape's unique massage table and its technological capabilities.

play_circle_outline Transforming Massage Therapy: Aescape's AI-Driven Innovations in Personalized Experiences Using Real-Time Biomechanical and Biometric Data

play_circle_outline Insights on clinical efficacy and general wellness benefits provided by the massage service.

play_circle_outline Unique selling proposition: combating consumer discomfort with traditional massage therapy methods.

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Transcript

Eric Litman, Aescape

Eric Litman

CEO Aescape

In this MedTech Unplugged interview, Eric Litman, founder and CEO of Aescape, joins theCUBE’s Dave Vellante to discuss how AI and robotics are redefining the future of wellness. Litman shares the origin story behind Aescape, a company born from personal need and built to address the growing labor gap in massage therapy with an AI-powered robotic table. He walks through the product’s evolution from deterministic algorithms to edge robotics powered by real-time biomechanical sensing and model-based personalization.

The conversation explores Aescape’s str... Read more

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What challenges did the individual face regarding their neck pain and massage therapy? add

What advancements have been made in robotics and technology related to understanding human bodies over the past seven years? add

What technologies are being used to enhance the massage experience and how does the human element contribute to personalized treatment? add

What is the purpose and impact of the wellness device being discussed? add

What percentage of American consumers are willing to get a massage from another person, and how does this relate to market potential for an automated solution in self-care and body work? add

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Eric Litman, Aescape

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Dave Vellante

>> Hi everybody. Welcome to our MedTech Unplugged series. My name is Dave Vellante. You're watching theCUBE and NYSE Wired's ongoing series. This is our media week on MedTech. We're talking about the aging populations, the intersection of that plus AI-fueled innovation, value-based outcomes. This is hot and heavy in this community, and of course the consumerization and personalization of healthcare. Really excited to have Eric Litman here is the founder and CEO of Aescape with an A. A great edge use case here. Eric, thanks so much for coming on theCUBE and being here at NYSE Wired.

Eric Litman

>> Thanks for having me. This is a great environment.

Dave Vellante

>> You bet. So founder, sole founder?

Eric Litman

>> Yes.

Dave Vellante

>> That's cool. A lot of times-

Eric Litman

>> Has its ups and downs.

Dave Vellante

>> I know myself, I was co-founder, but you have superpower. I guess you've got both sides of the brain, but why did you start Aescape?

Eric Litman

>> It was literally a personal pain point for me. So I've been building tech companies since the early '90s. Sold my last company to a large publicly traded business back in 2015. Spent a couple of years integrating the business, living on an airplane, and I ended up with a bulging disk on my neck that just took me out of commission. I spent eight months of my life where I needed a massage every single day just to be able to turn my head as I solved my way through a medical issue. And my frustration was that I wanted something very, very specific and most massage therapists wanted to give me the protocol that they thought would be most helpful. It wasn't what was helpful for me. What was helpful was an elbow in one spot on my back for an hour every day. So it was just out of frustration that I said one day, maybe I should just automate this, maybe there's a solution that doesn't just exist for me. Maybe there are other people like me out there. And when I started looking at the category, massage therapy in the U.S. is about a $20 billion a year segment that wanted to be about 4 billion larger, but there's a substantial labor gap out there. People just aren't going through the process to become massage therapists anymore at the rate at which they once were. And the people who regularly get massage are typically in it to go fix something with their bodies. So the idea was build out a solution that's personalizable, build out something that I could get what I wanted out of, and hopefully the rest of the market would come along.

Dave Vellante

>> Now what year was this that you sort of had this idea?

Eric Litman

>> This was 2017 when I started this.

Dave Vellante

>> So just a couple of years after you exited?

Eric Litman

>> Yes.

Dave Vellante

>> And well before the AI heard around the world?

Eric Litman

>> Correct.

Dave Vellante

>> Okay. But you were using machine intelligence at the time, obviously, and it was what deterministic AI? Maybe you could describe what the state of technology was then, and I'm really interested in how far you've taken it.

Eric Litman

>> Yeah, look, we've seen tremendous progression in the technologies that enable robotics, that enable understanding of human bodies through sensing through other systems in the last seven and years. So where we started is nowhere close to either where we or the market are today, largely deterministic to begin with, now moving increasingly into model-based approaches to understand, to comprehend and to deliver. It's been a great technology journey and candidly, we've been buoyed by the rising tide that's lifted all the companies in the sector.

Dave Vellante

>> This is amazing. So Aescape is A-E-S-C-A-P-E. Search it and you'll see this device that you've created. What do you call this system?

Eric Litman

>> We call it the table. The Aescape table.

Dave Vellante

>> The Aescape table?

Eric Litman

>> Yeah.

Dave Vellante

>> Okay, cool. And this is a great example of AI-driven personalization, the consumerization of healthcare. Talk about the data aspect of this. What kind of biomechanical data, biometric data are you collecting and how is that used essentially in real time?

Eric Litman

>> So we have a host of sensors that help us to understand very specifically the person that's on the table getting a massage at any point in time. We have sensors overhead that scan, model and create a computational model of the body, and then the arms themselves are able to feel the body as we move along. We know when you breathe, we know when you move. We've been able to do real-time tissue stiffness discrimination and really start to gain a picture of the musculoskeletal data that's most relevant to you as a consumer of this. But there's another element that we came across along the way, and that is that with all of the technology we have at our disposal, and we are increasingly adding greater sensor density, sensor fidelity, more ability to acquire data, having the human in the loop was the key unlock here. Empowering you to say, I want this, not that. I want more of this thing, I want more in this direction. Ultimately, it allows you to build the treatment, or I should say the massage that is specifically the thing that your body wants at that point in time.

Dave Vellante

>> So you're able to interpret context in real-time with that human in the loop. So using generative AI, I speak to the platform, how does that work? Or is it, like you said, sensing my breathing, my moving, my tensing, all of that?

Eric Litman

>> Yeah, so today you use an interface where as you're laying on the table, there's a big touchscreen in front of you that shows off a 3D model of your body in real-time and where the massage is working on you at any given point in time. So you're very well-informed about what's happening to you and what will be happening, and you're given a set of controls to change that. Over time we'll continue to evolve that we'll make it much richer, much more interactive, and the sorts of things you're saying are very near and dear to our heart.

Dave Vellante

>> You've got, what? Dozens of sensors, you've got semiconductors throughout this thing.

Eric Litman

>> Correct. Correct.

Dave Vellante

>> So I presume it's not the latest, greatest, most expensive GPUs. They don't have to be, right? I mean, they can be, I don't know, N minus one, N minus two semiconductor type stuff you'd find in automobiles, very sophisticated, but low cost, low power, able to respond in real time. Maybe you could talk a little bit about your architecture.

Eric Litman

>> Yeah. We have what feels like a very modern edge robotics compute platform. We have a series of compute capabilities that allow us to run our perception, our control, our motion planning, all the user interface, and we take advantage of technologies that others in the market do as well. And much of what happens to drive that happens in the cloud where we do have access to greater storage, greater compute, and we'll continue to leverage that architecture over time.

Dave Vellante

>> Okay. So you have to balance the real time latency with the modeling in the cloud. Well, how do you do that? Actually, I can generally understand how you do that. I'm more interested in how that's changing over time as the on-prem device gets more powerful and you don't have to go to the cloud. How are you balancing that with cost and performance?

Eric Litman

>> Yeah, I think the majority of compute that will happen in the space of robotics will be model development, and that's all in advance of deploying anything to the edge. To your point, as edge compute becomes more capable, as models get better optimized for deployment, and you're dealing much more with inference and test time compute, the compute capabilities there can be particularly tight for the application. And ideally, you can increasingly do more and more without having to go back to the cloud. Right now it's a tightly-coupled architecture.

Dave Vellante

>> What have you learned in terms of just clinical efficacy, whether it's pain reduction, motion gains, I mean in your particular case you have a great use case. What are you seeing there and how is that evolving?

Eric Litman

>> So we've very intentionally brought this to market as a general wellness device, and so we think of it in context of that. General wellness devices for massage allow people to think about their stress, to think about general pain, aches, athletic recovery. And so our members, the people that get massages from us, all speak about us in those terms. And we hear great success stories of people who come in and they either improve their athletic recovery and athletic performance, or they are able to manage their bodies and the chronic issues that we all have as we get older in a way that's more challenging without us.

Dave Vellante

>> We had AI and Robotics Leadership Summit out in Palo Alto, but just about a month ago with the NYSE Wired, and we had sort of two diverging sort of thoughts on this. One was, "Hey, we're going to have these general purpose robots. They'll cook for you, they'll mow your lawn, they'll cut your hair, they'll do your laundry." Versus we're going to have these specialized robots, which is clearly the example of what you guys are in. Lower cost, more specialized, but more narrowly focused. So I'm fascinated in the business model here. What does the cost look like of actually producing these things? I think I'm correct in that I go somewhere to make this happen as a facility. So explain that and I've got some follow

Eric Litman

>> Ups. Okay. So look, on the first point, I think it's a really interesting discussion of whether or not we'll go generalizable and specialized. I think the answer is it will be both. There is a reason that forklifts don't look like people. We build specialized hardware for special applications because physics drives a lot of the decision making behind that. And I think in categories like ours, you're going to continue to see very mission specific robots that will outperform a generalized platform. Having an arm hooked to the base of a table provides a kinematic structure that can outperform what a humanoid structure can do because we can work on both sides of the body simultaneously. So that's that track. Going back to cost, we are relatively new in market. We've been in market now for about 11 months, and we've been aggressively working on bringing the cost to manufacture our robots down. The key initiative for the business, and we are very successfully driving costs out of our robots, which then empowers us to deliver them at a lower price point to our partners and then ultimately continue to democratize access to the solution for consumers. Luxury was the entry point for us because it just makes sense when there's scarcity involved, but really the goal here is to bring this sort of great personal care to as many people as humanly possible. So we're going to continue to make it mission number one for us to drive out the cost of this so that this can be accessible everywhere, and then a regular part of your fitness regimen, self-care protocol rather than something you just do ad hoc or when you really need it.

Dave Vellante

>> So a couple of follow-ups, if I may, Eric. So the Aescape platform, you've purpose-built it for the use case? It's probably much better than an elbow. We use the elbow out of necessity.

Eric Litman

>> I'm biased, but I think it's a hell of a lot better of an elbow.

Dave Vellante

>> We use it out of necessity, not because it's like anatomically perfect for massage therapy. Okay. Then the business model for your partners, your distribution channel, is it part of a health club? Is it a subscription model? What are the patterns you're seeing there or is it all consistent?

Eric Litman

>> We have partners that are exploring a number of ways to bring it to market. So we license the product out to businesses that want to deploy these, and we do that in hospitality. For us, hospitality is hotels, it's gyms, corporate offices, multi-family dwellings. We think about the athletics category, so pro sports teams, collegiate leagues, venues. We are in the healthcare category increasingly. So bringing these into chiropractics, physical therapy for massage purposes in those environments. And within them, they all operate a little bit differently. They think about their consumer a little bit differently. Some of them charge on a per unit basis, they'll charge for a straight-up massage. Others are now beginning to roll out subscriptions where because the marginal cost to deliver a massage on our table is so very low, utilization becomes the key factor. They just want to drive more people through and even perhaps extend operating hours and be able to see more people throughout the day. And others still are baking it right into their membership model.

Dave Vellante

>> Airports, malls, you see these, whether it's chairs, foot massage, massage chairs, you see physical humans in airports now, is that-

Eric Litman

>> Potentially in lounge environments? I don't know how well massage does as a category in airports or in malls.

Dave Vellante

>> I have no idea. I've never known that.

Eric Litman

>> I don't think it does particularly well. So it's just, I think for us it's really more about having the tables in places where it just makes sense where it's going to fit into your workflow. Where a 30-minute massage is something you can easily accomplish, particularly given that with our massages, you're not showering, you're not oily, you get to go in, get it done, get out very quickly. It's a very efficient play.

Dave Vellante

>> How do folks get paid? If in the medical world, obviously payers will pay for health outcomes, if you can show that, is there an angle there for your partners?

Eric Litman

>> I think that's early for us. I think we will start to explore some of that in the coming months and years. But today, it's a general wellness device and consumers are opting in because they're making their own value judgments about what it does for their bodies. And for many people, the modality of physical engagement and soft tissue manipulation is something that just improves the quality of their lives.

Dave Vellante

>> And it does, and it improves your healthcare, but it doesn't seem that the system is open-minded about that. But maybe that'll evolve to a point where if you can demonstrate better health and lower cost as a result of that better health, certainly in your case it is proof. Perhaps it can fit into the payer system at some point.

Eric Litman

>> And where I think it could potentially fit in is in a world that's increasingly moving towards capitated payments, we at some point in time demonstrate efficacy to the physicians involved in the ecosystem that this can drive a favorable outcome for them at a better set of economics than what they're doing today. And they opt into using this, just that part of the protocol.

Dave Vellante

>> The physicians have some weight there as a voice. What about the regulatory climate, FDA approvals, things of that nature? How are therapeutic robots sort of fitting into that scheme? So we don't think of these as therapeutic. We think of them as general wellness devices. And we work hard to stay within those boundaries. We're not making any specific claims about what this can do outside of what a general wellness device would do.So in other words, regulatory frameworks are not a blocker for you, is that right? Because of the positioning of the company and the product? Is that right?

Eric Litman

>> We've had to go through a number of certification processes. So we've gone through UL. We've built the product to be tested and safe and to fit within the bounds of a general wellness device.

Dave Vellante

>> How reliable are these systems, Eric? How do you deal with preventive maintenance, hopefully not doing truck rolls, phone home? How does that all work?

Eric Litman

>> So the devices are connected devices, so we manage them, we fleet manage them. Within our team, we've built a number of tools for the automated maintenance of them, and we're increasingly automating that. And then we have a nationwide network of technicians that are capable of going out and removing a component if something has an issue. The good news is robots in general tend to be very well-characterized pieces of hardware. You have a pretty good idea of when they're going to fail over time. Most of the other components are reasonably, there's not a lot to break in this and they perform well.

Dave Vellante

>> And on the regulatory framework, is that the same with data privacy that you're not subject to sort of HIPAA and things of that nature, so you kind of avoid that whole blocker. Looking back to cost, do you have situations where individuals actually will purchase these things? What is one cost?

Eric Litman

>> It's not a primary market for us, but we do have some folks that have been-

Dave Vellante

>> Is it tens of thousands? Is it hundreds of thousands of dollars?

Eric Litman

>> It's closer to the latter, yeah, it's $150,000 to license one of these into the home.

Dave Vellante

>> Okay. So you've got to have a business model to offset that cost, but the cost that will come down as your manufacturing volume increases, right?

Eric Litman

>> And if you're a business, if you're not bringing into the home, it's a monthly licensing fee on an extended contract. So it's in the neighborhood of four to $5,000 a month.

Dave Vellante

>> How did you fund the company? Do you feel like you have product market fit, and at what point do you scale go to market?

Eric Litman

>> Yeah, so we've raised about $130 million along the way from some top tier investors, including Valor Equity Partners. They're the earliest investors in all the Elon Musk's companies. They're big in the space of deep tech and the hard tech. They've been a great partner for us, and we're continuing to scale. We absolutely have product market fit. The product delights consumers every day. We have partners that are making money repeatedly off of this, and we're now going to market to go raise our series B in the next couple of weeks.

Dave Vellante

>> Are you predominantly North America? Are you overseas?

Eric Litman

>> We're U.S. only at the moment will begin international expansion next year.

Dave Vellante

>> So where can I go to actually experience this? Because when I was searching and prepping for this, it was like, I want in.

Eric Litman

>> All right, great. Let's get you in. We're all over the city here in New York. We have about 1000 locations across the country. So if you go to Aescape.com, A-E-S-C-A-P-E.com, you can go to the booking system, find a location. The great news is we're in some really, really nice partners that offer a series of amenities associated with this that don't require a membership. So if you go to an Equinox and book at an Equinox or a Life Time Fitness or a Ritz-Carlton or a Four Seasons, you get to take advantage of all the other lovely things they have around them without being a member. It's a great way to go experience the product and have a treat yourself moment together with it.

Dave Vellante

>> So it's a $20 billion TAM, but it's constrained by human labor. And so the TAM could be enormous here. I mean, the need is... I these devices could be everywhere. It can be hotels, they could be in look apartments around New York City and they've got gyms. I mean, why not put one of these devices there? When there's demand, put more of these devices. I mean that TAM could double or triple, who knows?

Eric Litman

>> So you've nailed it in that we can grow the market by bringing in more capacity. But here's the really interesting point. Only about one in five American consumers are willing to get a massage from another person. They're uncomfortable with something about their body, they're uncomfortable with strangers, they don't want to be nude to the stranger. You ladder up all those issues and it adds up to about another 80% of the market. And we've been hearing consistently from consumers that they're open to regular self-care and body work from an automated solution. Turns out about half the people now, about 50% of the consumers are regularly used Aescape are not endemic to the category. These are new people that have integrated this into their lives. So I agree. I think there's tremendous upside potential.

Dave Vellante

>> This is true. I mean, I've talked to women who say, I don't want to get a massage from a man. I've talked to men who say, I don't want to get a massage from a man, whatever. But so-

Eric Litman

>> Some people don't even want to have to be asked that question, so they avoid it altogether.

Dave Vellante

>> Eliminates it. Well, of course when you're getting a massage, you're like, Hmm, I wonder who I'm going to get. What do they look like? Are they tall? Are they small? Are they this or that? This eliminates that and it sounds like it's more effective. So, all right, where do you want to take this company? Where you talked a little bit about that, but what's the big vision?

Eric Litman

>> This is just the beginning. So what we've done is we've solved the really hard set of problems needed to have robots safely and autonomously interact with human bodies. It's an incredibly hard set of problems. We are executing very well right now on delivering massage therapy into the market, on building the consumer awareness around this, on really learning how to optimize the model of getting people comfortable with this, getting businesses to deliver it and adopt it, to market it, to build the market around it. Next for us is then leveraging all of that, the data behind it, the consumer insights, the human-robot interaction models into other categories where robots can safely interact with human bodies. Massage is just the start.

Dave Vellante

>> Oh, this is an exciting time. We hear Jensen talking about it all the time. Humanoid robots and special purpose robots. We're super excited, Eric, for this future. So thanks so much for coming to theCUBE-

Eric Litman

>> Thanks for having me.

Dave Vellante

>> And being part of NYSE Wired. You're welcome. All right, keep it right there. MedTech series. This is Dave Vellante for John Furrier, the entire CUBE and NYSE Wired team. Keep it right there. We'll be right back right after this short break.