113. Inside Inspiren: Practical AI for Better Care

In this episode of Raising Tech, Matt sits down with Inspiren’s Brian Geyser and Michael Wang, two clinician innovators aiming to transform senior living with a fully integrated, AI-driven care platform.

Brian shares his path from nurse practitioner to industry innovation leader, while Mike walks through his powerful journey from Green Beret to bedside clinician to founder. Together, they break down why senior living still struggles with tech adoption, how to make AI truly useful for caregivers, and the critical role of co-innovation in building tools that actually work.

They also dig into Inspiren’s vision for ambient, predictive technology, from better documentation and workflow to a future where falls become genuinely rare.

A quick, insightful look at where senior living tech is headed next.

Learn more about Inspiren on their website.

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Transcript

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Matt Reiners: [00:00:00] Welcome back to another episode of Raising Tech. I am so excited for this episode. I'm joined by Brian Geyser, the head of Clinical Innovation, and Mike Wang, founder and chief clinical Officer, both from Inspire in and before I have them introduce themselves. Um, you know, from Brian was probably the first innovation person I ever met in the industry.

I think anything I've ever been introduced to. Whether it's innovation or technology was really, uh, spearheaded from him. So I, I owe a, a lot of credit to where I am today due to Brian. Um, you know, he won't admit it, but don't ask about his basketball game on this episode. Um, and then also with Mike, uh, Wang, who's the founder, chief clinical officer.

I've gotten to know Mike over the last year, 18 months, and just love the energy, love the passion, [00:01:00] and love the story, and, uh, love how you guys are coming in and really transforming senior living as a whole. So, thanks for joining me today, gentlemen. 

Mike Wang: Thank you for having us, and you're not the only person to talk about that, uh, about Brian.

Uh, I am very much also in that boat. Uh, I wouldn't be where I am without Brian. He was the first person in senior living I ever met. Uh, and, uh, also, uh, the very first, uh, client. In senior living, uh, for inspiring. So, uh, you know, I, Matt and I have a lot in common in, uh, owning a lot to Brian. So Brian, if, if that doesn't, if that doesn't make your head, uh, yeah, I'm out here guys.

Brian Geyser: The ego's getting bigger, but, uh, my, but my ego will deflate by the second as we talk about that basketball game, Matt, because. As much as I hate to admit it. You, you crushed me. 

Matt Reiners: Hey, I, we all have moments in our life when we peak. Brian and I peaked there, so, you know, it's, it's, it's been downhill ever since.

But, [00:02:00] uh, but no, I'm, I'm really excited to jump into it and I, you know, wanna give you both the opportunity. I think, Brian, we start first with you. Like, what is your story and how did you end up where you are today? 

Brian Geyser: Uh, boy, uh, uh, yeah, so the short version is, uh, I'm a nurse practitioner by training. I've been in healthcare for three decades plus, and, uh, I have moved throughout the healthcare system.

All over the place from hospital, emergency department, outpatient, inpatient, uh, and, uh, and, and a big chunk of my career has been in home-based and community-based care. Um, my first job actually as a nurse was in, was in home care. And, uh, and then I, I, when I became a nurse practitioner, I started a group psychiatry practice and ended up servicing senior living communities.

That was my first foray into senior living. And, uh, I have been in senior living in one way or another ever since. And, um, you know, w was recently at Maplewood, uh, and, uh, did about eight [00:03:00] years there in clinical ops and innovation. And, uh, along that path I met Mike and. Uh, was really, really impressed by, by him, his background and, and the, uh, the company that he started and the product he invented, which I'm sure he can talk about.

Uh, but the big thing was the impact that the, that his technology was making, um, in the hospital space early on in Inspire. Early days, and I saw that the, uh, the impact it could make in senior living and started to talk about, uh, how, you know, how Mike might wanna make a pivot into senior living with the product.

So, uh, that was, that was the early, um, connection to Mike. And we've, we've maintained, uh, a relationship ever since. And then ultimately, um, you know, I, I decided it was time, you know, with ai kind of like taking over the world. And seeing what could be and seeing the, the potential impact across senior living with technologies like [00:04:00] what Mike had, uh, developed.

I decided this was, this was the time, if ever there was a time to make a pivot in my career, this was it. So, um, you know, fairly recently, I, I, I made the jump over to inspiring and I'm, I'm with the team now and I'm super excited to be here and, uh, happy to talk about what we're gonna do to transform the industry.

Matt Reiners: I love that. And uh, it's a perfect segue into you, Mike. 'cause you know, Brian first connected us. He's like, yo, Mike's super cool. He is, got an awesome story. They're doing some really cool stuff. Um, rather than me trying to remember that conversation, wanna share a little bit about your story and how'd you end up where you are today too?

Mike Wang: Yeah, absolutely. I definitely was not a straight line in terms of, uh, the trajectory of my life. Uh, first career was in the military. I spent seven years. Uh, serving as a Green Beret. Uh, after the war in Afghanistan, I came back home and chose nursing as my civilian path of service and specialized in geriatrics and cardiothoracic surgery, eventually becoming a nurse practitioner.

And I came up with the idea of [00:05:00] inspiring, uh, from the bedside, uh, from the frustrations I experienced as a clinician, and also just the complete lack of data. In the care process, uh, that impacted negatively, uh, in terms of safety, operational efficiency, and uh, clinical efficiency. Uh, so it was a wild idea.

Uh, and I kind of saw the coming of ai. 'cause back in 2016, nobody was talking about ai. Uh, really kind of saw the coming of it and I thought, let's build towards it as opposed to try to catch it when it actually explodes. So. I was fortunate enough to be able to work with some of the very best in the world, uh, to really bring the idea into fruition.

If you look at the total number of technology companies in healthcare, that's hardware and software, uh. Uh, with someone with zero finance, uh, uh, technology or building technology experience, uh, for us to be where we are [00:06:00] today, the, the probability's probably less than 0.1%, so I'm extraordinarily lucky and fortunate to be able to meet folks like you and Brian and just really in my own way.

Believing in the mission of changing the world in terms of bringing a technology that can prevent death and suffering. And to me, there's just no greater mission than that. That's what gets me up in the morning every single day, and I'm just extraordinarily blessed, uh, to be able to do what I do and be in love with what I do.

Matt Reiners: Well, I'll say, you know. It's rare for me to be on a call where like, I think I'm pretty cool. You know, I'm arguably cool dad, but you guys are way cooler than me and Mike, thank you for, uh, your service first and foremost. Thank you. But you know, and I know you kind of touched on getting the idea for Inspiring Bedside, and I'm just wondering, like, of course, you know, we're gonna talk more about the industry, but what the heck is inspiring?

Mike Wang: Yeah. So I, inspirin is the [00:07:00] first technology platform that build. A full e ai ecosystem for senior living, specifically for senior living. It is a combination of physical AI and, uh, software AI that really impact the safety, the profitability and operational efficiency of senior living operations. Uh, so our technology is completely proprietary and we built it customized for the specific needs of senior living.

And it is driven from the perspective and input of the clinician. Our company is very much still clinician driven. Uh, really prolonging the ethos of clinician driven culture as well as clinician driven innovation. I think that that is probably one of the biggest differentiators, uh, for us, and it has really paid dividends in terms of being able to allow every functionality of the technology to benefit the caregiver and ultimately, [00:08:00] uh, the residents themselves.

Matt Reiners: Yeah, I love that. Um, and it's, it's such a needed thing and you know, obviously you guys both bring deep clinical backgrounds into tech, which is just so cool. And I think just such like a, a rarity within itself. Right. I know you had mentioned that before, but I'm wondering like what patterns or problems really in this patient care, especially in senior living, first convinced that you need, that technology needed to evolve and either of you can take that.

Mike Wang: Well, I'll, I'll let Brian, uh, take it because he was on that side of the operator and he saw it and lived and breathed the problems. Uh, so I'll, I'll let Brian take that one. 

Brian Geyser: Yeah. Before I jump into that, I just wanna mention that we've got, uh, over 25, uh, RNs and, and some PTs and OTs on our staff as well.

So we are heavily nursing focused and we talk about, uh, clinical care delivery. We've got, um, amazing, uh, talent, uh, that we bring to our operators. [00:09:00] And we walk with them completely on the journey from beginning all the way through. We never stop. We're with them all the way through. So it's really nice to have so much nursing talent and clinical talent, uh, bringing this to the industry.

'cause we all, you know, what we know and, and this speaks to some of the, the giant gaps we're trying to solve for, is that residents are, are aging, much more frail, lots of chronic conditions, lots of medical complexity. Um, we're taking care of them in a nonclinical environment. But, but make no mistake, there are.

Massive clinical, uh, needs in our residents and care needs. And we, we, uh, as an industry need to figure out how we're gonna solve for that. Um, when, when I was in clinical ops, one of the, there were so many things that I was trying to solve for. One of the things is that, um, we we're, we have no idea, to be honest, like, what's going on with our residents when they're behind those closed doors.

You know, they, the, these are, uh, very frail, older folks who many, many of whom have [00:10:00] cognitive challenges, lots of physical challenges, functional, uh, challenges. And when they're in their own, uh, apartments, we have no idea what's going on with them. And that's, that's a big problem. Uh, we need to understand what's happening with them so that we can provide, uh, you know, pinpoint precision level care to them when they need it.

Um, and that always worried me. The other, the other interesting thing is we, we have really little idea how much time our staff were spending with our residents. The way that the industry works now with care plans is we, they're all task-based. So you have, you have one resident who requires, you know, maybe four showers a week in order to meet their hygiene needs.

Uh, and another resident who also requires four showers. But we have no, no idea how much time those showers were taking. With, with, uh, with the first resident, we might be spending, you know, 45 minutes, uh, every single shower. The other resident might take 20 minutes, but we, we didn't, we didn't know that, [00:11:00] and therefore we're not able to fully understand the cost of care delivery for each individual resident.

And that was a big problem. So I think that's a big, a big challenge to solve for. Um, you know, our, our, our point systems and our care leveling systems are very arbitrary. Uh, and, and they don't really, they don't really make sense. So I was always trying to figure out how can we add the time component into this so we really understand.

The frequency of visits to the apartment, the duration of those visits, how complex is it when we go into those apartments? Are we having to put two or three staff members in an apartment and to take care of a resident and get their care needs met? When you do that, you double or triple the cost of care for that resident, but it's nowhere is it reflected in the the costs that we're charging them.

So there's a big, huge gap there that, um, that I saw Mike's technology could solve for, and that was one of the things I was super interested in. We, uh, we, we all, we're also terrible [00:12:00] at documenting care. About 50% of our care is never documented. And that's, that's unacceptable for so many reasons. You know, there's, uh, there's loss of, of financial viability with that.

There are, there are, uh, compliance issues. There's regulatory issues. Uh, that can expose you to lawsuits and things like that. So we need to get better at how we document care. And we're working on all of that too, is like, you know, we want to get to a place where documentation is passive and ambient. You don't even have to do anything.

You know, the, the, the, the apartment itself knows who's going in there, what they're doing, and it's documenting it right into the record. So there were so many gaps we have in senior living and so many things that we have to solve for. And, uh, inspire's technology. When I saw it for the first time, was the first time I had seen something that actually could help us close those gaps.

Matt Reiners: Yeah. No, I love that. Um, and, and you know, it's so funny when I think about technology, right? Because like, and I've seen this [00:13:00] firsthand from my background, but like, there's often this disconnect between innovation and adoption. Um, you know, I think I see more and more companies are trying to break into senior living.

They've got the most innovative product and they want to do this, but the adoption is, is lagging and it just loses its stickiness and kind of falls off of a cliff. Um, and I'm just wondering like, how can you. And probably either, either of you can take this question. Um, how can we build systems where, like tech supports rather than just replaces compassionate care and that we can continue with that adoption for the long term?

Mike Wang: Yeah, it's a, it's such a great point because both Brian and I have experienced cases where a piece of technology was putting our hands and it was very obvious. The people who developed it did not understand remotely what it's actually like to use the technology in a care environment. I think that's the biggest issue is many times it's a bunch of [00:14:00] engineers or finance people that have identified a technology was capability and they say, Hey, how do we make this fit into healthcare and make a bunch of money and, and make sure that people, uh, use it.

Right. Many vast majority, uh, of the technology companies, uh, kind of originate that way. It comes from a boardroom. The most important thing about adoption is you actually design the technology from the perspective of people who are actually using it, right? I think that perspective is the most powerful because it guides you.

In designing that technology every step of the way to make sure by the time you put it in the hand of a caregiver or an operator, it makes sense to them. Mm-hmm. It's intuitive. We're not in the business of [00:15:00] adding additional things for people to do, and also we're not in the business of disruption. So that's one, uh, myth I really want to dispel here is disruption is not a good word.

Uh, for, for our industry. Uh, we should make. Technology that are not disruptive, allowing the workflow and the experience to be absolutely seamless and intuitive, that ultimately is what drives adoption. The ease of use and understanding why this piece of technology benefits me as a caregiver, as someone who's on the front lines actually using this technology.

That is the most important part. So not enough technology companies come from the, that perspective. So one thing that we lucked out on was that was the only perspective that we knew. Uh, there was the only, uh, origin place that we could come from, and that has been the centerpiece of inspiring and, and [00:16:00] everything that we do is from that perspective.

So I think from, from that, from that uh, angle, uh, we really. Should, um, give a lot more input and put the innovation as an integral part of the clinical team and the then the folks who are actually using it instead of just clinical consultants that come on and look at a product and so on. So I think from that perspective, innovation from a clinical perspective is the key.

Brian Geyser: Yeah, we, we, I'm, I'm building out this framework for this that I'm calling, have used DO or HUD for short, not housing and urban development, but have used, do so that the have frame, the have, part of it is you have the tech, that's the easy part. You own it, but you're not getting any, uh, value from it. It's, it's latent value or unrealized value.

And we, we had this issue when I was in operations where we had a piece of technology and it might have been a good technology. But we weren't, we [00:17:00] weren't using it. It was like either sitting on a shelf, gathering dust and we're paying for it. And, and you think to yourself, well, how could that happen? Like what happens there?

Well, it happens for so many reasons. One of the reasons is because of the turnover in the industry. You have so much turnover that the tech may, may, may have been used pretty well. Uh, and then you lose a director of nursing or you lose, uh, experienced director. And then the thing just sits on the shelf because the new person coming in didn't even know it was there.

So not only do we have to have great tech, we have to have people, uh, in the tech companies that help, uh, guide and hold the hands of the operators throughout their entire journey because their journey is tumultuous and it's chaotic and it's, uh, a a lot of craziness coming out at them all the time. So you have to hold, hold their hand through that process.

The, the second part of that is the use phase. So the use is when you know you, you're using the tech, it's functional, but there's friction and it almost feels like I have to use this [00:18:00] because somebody gave it to me and it's part of my job. It's not really doing much for me, but I have to do it. And that you don't wanna be stuck there.

It's better than just having it and not getting any value out of it. But, uh, we wanna get to the next place. And that's the do phase where you're just doing the tech. It's just in the background. You're just doing your job better and you're not even thinking about it. And the analogy I use there is, is the, the engine in a car, right?

The engine in a car is an unbelievably powerful piece of technology, but we never think about it. We just get in our car and drive. Right. So it's the same way with the tech that we build it. It should be something that you, you barely ever think about, but you're just doing your job better with better outcomes and proof of that outcome.

Yep. Yeah, 

Matt Reiners: I love that. And you know, to your point, Mike, some of these decisions are being making in a boardroom. Like, it's so funny, like, I've worked, or you know, I've consulted with some companies out there that they see the business to business play of going into senior [00:19:00] living, right? They're reading about these demographic age shifts, and they see this as like, oh, we could just easily create this technology, put it in here, and it's gonna go gangbusters, and then they, it just falls flat on its face and it happens.

So many times. And you know, Brian, to your point, it's, it's, you know, thinking back to my own, uh, experience, you know? Yeah. How do they implement that hud, because I saw so many times people having technology, there's a turnover, people that aren't fully understand. I remember going into a community with our technology and one of the staff members at one point was like, is this for us?

And I was like, oh my gosh, I suck at my job. Like I need to do better of like, how can I. Help, uh, their residents. Um, and Brian, I know one of the things that's always stood out to me from your perspective, especially as AI has taken over the world, is like how, you know, you, you talk about how do we make use technology to make care more human?

And I'm just wondering, like, if you could just kind of talk about through that mentality when it comes to that. 

Brian Geyser: Yeah, the, the whole goal is to be able [00:20:00] to, uh, provide tech that allows humans to do what humans do really well and let the tech do all the other stuff. So all this repetitive action things that are, uh, you know, stuff that we do over and over and it's rote.

We shouldn't, we shouldn't be having to do that. And, and documentation is a perfect example of that. We need to get to a place where documentation's fully automated. And that allows the caregiver to spend more time with the residents doing what they do. We want to free up the empathy is a good way to put it.

So, uh, humans are really good at empathy. And when we think of our frontline care staff, the vast majority of them are wonderful human beings who really care, but they don't have time to care. 

Mike Wang: Yep. 

Brian Geyser: We need to give them that time. And the technology is a good way to do that if you do it right. So it's, to me, it's a, it's, it's all about the, it's, you know, it's the humanity aspect of tech.

The tech fades into the background and that allows us humans to do what we do really well, which is think about people, [00:21:00] care about people, do the right thing by people. And if, if our caregivers are. Stuck in this wheel where they just can't even get anything done. They're running around, they're, they're spending half of their shift trying to document what they did for the, for the, uh, resident.

Then they're not spending that time with the resident and that's not acceptable. We've gotta move to a different place. Yep. 

Matt Reiners: Yeah. And one of the sayings I always like to, or like mantra is I like to say in all my talks when it comes to technology, because I talk a lot about AI in the conference circuit, but I always come back to this, uh, this thought of like automating the mundane to elevating the meaningful.

Um, you know, each person, the meaningful might mean something different. I do think, you know, the majority would kind of define that as time spent with residents, right? Those one-on-one connections, those relationships and how can you use technology to act smarter? Kind of cut out some of that burden.

Administrative task work that we all have to do, um, and allow us to do what we're hopefully good at, which is being human right. 

Brian Geyser: Um, I can, I can give a, a [00:22:00] specific example of, of how our tech does some of this and, uh, so when, when our caregivers get in in the morning and they grab their iPhone, uh, the last thing you want to do is have them grab their iPhone and have to have to log into like, you know, five different apps to do their job.

So you want to get to, to the place where they're using one app and they're using it throughout their, their day. But with, with the tech that we've built, like our caregiver can come in, they can assign themselves to their residents. And then they can view the residents in their environment. They could see at seven in the morning, five of my seven residents on my assignment are asleep.

Two of them are up and about. Now I can prioritize my workflow. I can say, I'm gonna go to those two residents. I'm gonna let my other five residents sleep. Yeah, because you don't want to be popping in on a resident and interrupting them if they're sound asleep. Sleep is critical for health and wellbeing.

And so that little simple insight that they have because of the technology allows, it gives them power in their hands to be able to say, I'm gonna go take care of those two because they're up and [00:23:00] about and I'm gonna let the other guys sleep. And that, that right there is humanity. I don't know about you, but I love sleeping in the morning and I don't wanna be interrupted.

Right? So who wants that? Especially in your own private environment. So thi this little thing that we do every day is super powerful. Yeah. 

Matt Reiners: Yeah. Well, I don't feel like we can't talk about sleep as I have a six week old right now is the time of, uh, filming this. So, uh, this is why I like zoom with the filter, so you can't necessarily see the huge bags under my eyes.

Brian. 

Brian Geyser: Hey Matt, I want to ask you about that. You have a six week, week old, right? You, you have any, any monitoring going on with that six week old? 

Matt Reiners: Of course we've got a nannette set up that we paid for the premium thing, so we know when he wakes up and we get sleep insights and uh, you know, he's still sleeping in the same room with us.

But yes, we, we invest heavily in that. And that's a great comparison. I love that, that thought process with that. Yeah. 

Brian Geyser: Well, all I have to say is why would we not be doing that with our most vulnerable older adults? Okay, come on. Yeah, like, like, we need to [00:24:00] know if. If they have, if they have a pulse, we need to know if they're breathing.

We need to know if they're safe. We need to know if they're okay. Same thing. And I'm not, I'm not trying to compare, you know, older adults to babies, like, gimme a break. This is, this is, we need to be thinking more strategically and smarter about this stuff. Of course, I want to know if my mom is okay, right?

She's in a senior living community. The number one reason I want her there is 'cause I wanna make sure she's okay. Right? So why don't we use technology to do that? Makes sense. As long as it's not, you know, infringing on their privacy. Of course. 

Matt Reiners: Yeah. Of, of course. And yeah, you know, I think back to of, you know, just being smarter, like, not so much with our six week old, but our first child, we had the bander around her that tracked her breathing and heart rate.

We'll get that when he sleeps in his own room. But I remember one time it went off 'cause it said it stopped breathing and we all ran into the room. Right. She was fine. But just to kind of give us that insight and we can, uh, you know, act appropriately. Mm-hmm. Um, and, and a question's probably for. Um, Mike, you know, 'cause from an [00:25:00] innovation standpoint, like, you know, I feel like innovation requires a risk of, or, you know, a tolerance, a risk tolerance.

Um, but like, how do you test and validate ideas quickly in high stake environments like hospitals or senior living communities? Yeah. 

Mike Wang: That, that is such a key part because if you get that part wrong, uh, your, your company is dead in the water. Um, innovation is is very tempting because you want to do everything and you want to cater to everyone and you want to make that impact in the world.

Uh, but how we do that is we have a very systematic validation process. Uh, we have to very systematically evaluate the need and use case. Uh, of that particular functionality. It has to come from the real world. Yeah. It cannot come from an engineering team that says, Hey, it would be really cool if we built this.

That can never be the case. It has to be a real need from the market [00:26:00] that's articulated across. The entire spectrum, meaning it can't just be one client. It can't just be one person thinking it's a good idea. Uh, it has to be validated across the board. And one great example of that is. The need for a fully integrated emergency call system that has, uh, fall for prevention technology, has care tracking technology.

Uh, one example of that is the market needing a consolidation of technology under one singular platform. Uh, one example I use is. Before the iPhone, uh, we used to carry around Kim Quarters, MP three players, cd, uh, the, the, the, the big bundles of CD that we, we used to carry with us. Um, it was a very fragmented market, right?

Um, but the, there was a need. Uh, from the population to consolidate all of that under one singular seamless platform. And, and that's exactly, [00:27:00] uh, what the message was from the market. And, and we delivered on that. Uh, so you have to listen to the market. You have to listen to the real world once again, cannot be made in an engineering room.

It cannot be made in the boardroom. It has to come from the real places. And also really. Get down into individual conversations. It is not just about speaking with the leadership and so on, but grab a caregiver, sit next to them and have a heart to heart and say, Hey, we're thinking about this functionality.

Do you find that helpful or do you think that's a useless piece of crap? Right? You need to be very honest. You need to be very direct, and you need to find out from the people. Uh, of just exactly how they feel about it and what, what is the absolute need. What we are always looking for is for a caregiver or someone in the front lines and say, if you take away this functionality, I quit.

Uh, that's an extreme example, of course, but that's [00:28:00] the kind of. Dependency that we want to see from a technology because they view it as such a valuable part of their everyday workflow. So it has to come from the real place, and you have to really go out there to find the answers. Uh, you can't rely on some research engine to, to help you answer those questions.

So you really gotta get out there and be in the trenches and really understand the needs of it. 

Brian Geyser: Yeah. Interestingly, uh, uh, in the recent argenti uh, technology survey they did with operators, uh, 86% of the operators out there said that co-innovation is the path to, to success. Correct. And that's really interesting.

So what they're saying is we don't want technology providers to come to us with a piece of technology that has not been co-innovate with us. Right. They, we need the voice of the customer in the, uh, in the design and development of the product. And, and frankly, [00:29:00] that's one of the reasons I'm here. One of the reasons Mike wanted me to come was to be that voice of the customer inside the company, helping our designers and our engineers, our developers build the products that operators want and need.

Yeah. Uh, so I, I'm, I may be the bane of their existence because I'm constantly saying, no, no, no, no, no. We're not doing that. Uh, or, or that's, that's okay, but we need to tweak it and do it this way. So that's part of what I, what I, my job is here. Uh, but I'm just an n of one, right? And so we still take all of this stuff out to the living laboratory in, in communities.

We work with operators who co-innovate with us and who want to be on the cutting edge, who wanna design the future. And we have, many of them are, some of the operators we work with are incredible partners, and they help us every day think differently about how we're gonna design the products and services that we offer.

Yeah, so I, I would say co-innovation. Is the path to transformation. You can't do it without that. Y [00:30:00] 

Matt Reiners: Yeah. And it's one of the things, and I'm, you know, I'm so happy to hear you guys say that. 'cause one of the things I feel like at times I, uh, preach at nauseum, it's just like how valuable client feedback, prospect feedback, working together on like what works, what doesn't work, you know, attacking it from not a point of being defensive, but, uh, a place of like, to call like genuine curiosity, right?

Because they'll. Working with the end user, right? Like go in there and say like, what's a piece of crap? What's not working? Yeah. What would make you be like, that's just the most valuable feedback any company can get, and I'm always surprised when companies don't embrace that and kind of avoid that. At times.

I've seen too many people like. Try to create something behind a closed door. Open up the closed door and be like, here you go. And everyone's like, this sucks. We don't want this. Right. So it's like, yeah, it that, that feedback loop is so important to the end user and everybody. I 

Mike Wang: think you kind of, you imagine as kind of a restaurant owner who doesn't speak to their actual diners.

Right. Who doesn't actually go out in the dining room to actually ask their feedback. What do they [00:31:00] like about it? How's their meal, how's the experience? And so on. Uh, you can get that from a survey. Uh, you really have to experience that, and that should be a very important data point, uh, that you put into the overall innovation process.

Yeah. 

Brian Geyser: One of the things you learned from, uh, Steve Jobs is what, what, what Apple was so good at was weeding through the signal to noise ratio so that there's so much noise that, that they could have developed. But what Steve Jobs would do is just laser focus in on the one or two things that they were going to solve for and, and just crush it.

Right? And so, one of the things that we do all the time, you know, there's 20 things that we could design and develop, but you can't do all of them well. So we listen to the operator say, what is the problem to be solved? Or what is the job to be done? And then we, we, uh, validate that across many different operators and then we laser focus on that and we solve that problem really well.

Matt Reiners: Yeah, I love that. And you know, and one of the things we talked [00:32:00] about throughout this conversation, and I know we, you know, joked about how AI is taking over the world and you know, it's obviously like the busiest of buzzwords I've ever seen. Like, not only in our industry, but across everything, in anything.

Um, I've also seen like it become a point of skepticism. I've almost seen like an AI fatigue, uh, where like people are almost like sick of hearing about it at times because I feel like. Too many times people talk about it and they're like, AI's gonna change the world. Like, yeah, we know that, duh. But like how are you actually using it?

Um, but I'm wondering like, how do you think about building trustworthy AI that doesn't overwhelm or confuse a frontline team? 

Mike Wang: Yeah, I think accuracy is key. Precision is key. Uh, you can not have a system that has large margins of error, uh, when you are. Building trust with the caregivers and so on. So I think, uh, accuracy, uh, absolutely.

So the sophistication of the technology, how you think through building of the technology is extraordinarily important. [00:33:00] Uh, and also it cannot interrupt their overall process. Uh, it has to be ingrained in the process without disrupting the process. If, if that makes sense. Uh, allowing them to intuitively use it.

Right. It's almost as if they were about to do something and they just wish they had that thing and you should be that thing, right? So, uh, so really thinking through that entire process, allowing ourselves to really immerse in the work experience, uh, I think that is absolute key. And building trust takes time.

It's not overnight. Uh, and also no technology is perfect. Right. So how do you communicate that? How do you ingrain that into the training? How do you be honest about it and say, Hey, the, the, the technology doesn't work a hundred percent of the time, right? But these are the things we're working on, and your feedback is so important to allow us to be able to do better and to build better, and so on.

That on [00:34:00] honesty has to be there. That vulnerability has to be there. Uh, so being transparent about it and to work closely with those who are actually using the technology and taking in their feedback, uh, is extraordinarily important. 

Brian Geyser: Yeah, I mean, let, let's face it. Today, AI is imperfect, but it's impactful, no question.

Um, I, I use it every day in my job. It, it, it gets me maybe 70 to 80% of the way there, but I, I have to be in there for that 30 to 20 to 30%, uh, using my brain and then sort of co co collaborating with the AI to, to make, uh, the best impact and get the best outputs. The other thing I would say is that. Uh, tech vendors or tech solution providers have a trust problem in the industry, no question about it.

Um, and that was validated through Argento. Again, you know, the 85% of senior living operators, and this is a plug for you, Matt, uh, 85% of senior living operators believe that they need a trusted third party to [00:35:00] evaluate what solution they should pick. That, that means we have a trust problem. It's also a signal to noise problem.

Again, there's so much noise out there, and I remember one of my biggest challenges as an operator was weeding through the massive amount of options out there that I had, and I, it was very challenging. It was a big time suck and I, and it was hard for us to determine, you know, there's 10, 10 companies out there that, that say they solve this problem.

Which one of them should we choose? And that can be really, really difficult. Yeah. So trusted third party is one way to think about that, but I, but I also think that, um. You know, you, as Mike was saying, it's honesty and transparency. We're not gonna say to you, we're gonna come and be a hundred percent bulletproof on everything we're gonna do.

The technology's not there. And by the way, you know, we, we give AI a bad rap because humans are flawed too, aren't we? We make mistakes, right? Uh, but AI is really good at certain things, and we should leverage it for the things it's great for [00:36:00] and, and give it a break knowing that it's not always gonna be perfect, but you know, it gets better and better and better.

The velocity of which AI is improving is astounding. 

Mike Wang: Yeah. 

Brian Geyser: Um, so we definitely have to embrace it. You don't want to be left behind. Uh, that, that's another big thing is, you know, every company, every senior living company out there needs to be embracing AI at some level, uh, because it, it will impact every aspect of your business as we move into the near future.

Matt Reiners: Yeah. And it's been interesting working with, uh, a variety of providers because we have many coming to us and be like, we wanna use ai. And we're like, for what? And they're like, we don't know. So it's like kind of I, identifying that problem you're trying to solve and then looking for, you know, solutions out there to kind of help solve that problem.

Right. And then taking it down that path. Exactly. And, and final question here. You both can take it, uh, whoever goes first, your call. But looking ahead, what's one bold idea or vision you have for the [00:37:00] future of aging care and what needs to happen in the next five years to get there? 

Mike Wang: Yeah, I, I have a very specific goal and I think this is an area where we can make a huge impact.

I envision a day where falls and injuries are a thing of the past. Uh, I envision a day where it is so rare that if you do have a fall or injury or something like that happen in the community, people are shocked. I think the technology and the sophistication of the technology, if we continue to do that.

We will become so good at predicting, uh, any potential harm or falls from happening that we can actually prevent a vast majority of it. I think that's what's on the path of inspiring, is a prevention focused approach to technology, which is really hard. It is really, really hard for me to predict that.

Matt, you're gonna turn your head this way [00:38:00] in the next two minutes or something like, like, it's really, really difficult to do. However, for the first time in human history, we have the capability to be able to do it and if we treat false like a disease, uh, and by no means is inspire's platform, just a false focus platform.

But it is one of the main things that we do. If you look at it as a disease to eradicate this disease that leads to so much suffering and preventable deaths, I think it is a worthy mission to accomplish, uh, in the next five years as the technology continues to grow and we play a much bigger part in protecting those who are the most vulnerable.

In order to get there, we have to keep at it. We have to keep at it. And in a certain sense, competition's great for that. When you have a bunch of players, uh, that are all working towards solving a singular problem from different angles [00:39:00] collectively, that's good for humanity, that is great for, for people in the market because it drives each other to be the very best that we can be and to think aggressively towards innovation in a way that that will get us to where we need to be.

So I think. I definitely think it is well within our reach to be able to do that in the next five years if we continue on this path and we continue to work towards solving that, that problem and eradicating that disease. 

Brian Geyser: And for me it's been the same thing for the past, you know, seven, eight years, which is.

Uh, the, the physical environment, the apartment, the building itself becomes, uh, of an integral member of the care team. So the, so it's, it's, it's through ambient sensing technology, ambient ai, physical ai, that the, uh, the building itself, uh. Understands what's going on with the humans in the building. Yeah.

And we can surface up anticipatory [00:40:00] intelligence, the type of stuff, uh, Mike's talking about. Uh, and, uh, we are working super hard to get to that place where, uh, just passively. Things are being collected and intelligence is being surfaced, insights are being surfaced, actionable things that caregivers need to know.

Uh, and, uh, we're, we're scratching, just scratching the surface, but it's gonna be a really bright future. And, and I would, I would call it three years, not even five. 

Matt Reiners: Yeah. 

Brian Geyser: Agreed. 

Matt Reiners: I love it. Well, Brian and Mike, thanks so much for, uh, spending some time with me here today. It's been awesome to see your story from afar and uh, yeah, thank you for so much energy, passion, just, uh, commitment to drive innovation in senior living.

So thank you. Thank you, Matt. Thanks for having us, 

Brian Geyser: Dan, the basketball court, Matt.

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