Harnessing Data to Redefine the Resident Experience

25NFC On the Road with David Sawyer 

Lisa McCracken: Hi everyone. Thank you for tuning into the NIC Chats podcast On the Road from the 2025 NIC Fall Conference here in Austin. Super excited to be here. We've got a new guest to the NIC Chats podcast, TSO Life, David Sawyer, founder, and CEO. I've got a whole bunch of questions. We've got 30 minutes and we're gonna cover a lot of ground. 

But for those that do not know TSO Life, I would love for you to give a little bit of background on what the organization is and any background on yourself that would be helpful for people to know about.  

David Sawyer: Yeah, happy to. So really high level, TSO Life we're a resident insight and a resident experience platform. 

Our whole goal is to help operators get as much data on their resident as possible, and then focus on turning that data into meaningfully improving the quality of life and quality of experience of the residents that live within that community. I started this company, believe it or not, in a dorm room in college to date myself a little bit, 11 and a half years ago.  

So before this I was sleeping through French class and failing some of those classes 'cause I was too busy focusing on building a company. And originally we started TSO Life as a legacy preservation company. After my grandmother passed away, I was at her funeral listening to her life stories and realizing I never got to hear many of those life stories from her. 

So we originally started TSO Life with the mindset of trying to record every senior's life story and pass them on to their future generations. 

Lisa McCracken: I didn't know this. All right. 

David Sawyer: But as part of that work and we began to interact with more seniors and we really found the senior living industry and we started to really focus on other problems for us to solve as well. And that's when I just thought back to my own grandmother's experience. She had a stroke and had to move into senior housing and she went into a SNF and she would call us up saying she has no friends, she's lonely, she's depressed, and we tell her, no, grandma, I'm sure there's things for you to do there, what are you talking about? And sure enough we'd go look at the community calendar and it was four hours of bingo starting at 12 o'clock and ending at four. And that was it. And this was a lady who had her bridge group of friends that she used to play cards with, she was volunteering at polls and she had so much life fulfillment that she was used to having, that she stopped getting it there and we just, as the family saw that social piece crashed and then the clinical side followed right around and she passed away within six months of moving in. From there it was really just retrospectively for me to look back and go, if she had that quality of life piece, if she was able to fulfill that same element of lifestyle that she was having at home, but now in the community, I truly think she would've been with us a lot longer. 

Lisa McCracken: 'Cause your world shouldn't get smaller because of your condition and so forth. So how can you continue to have what you had, be who you are in the senior living setting? I usually, before I talk to people in the podcast, I go and spend a little time on the website and digging around and so forth. There were several descriptions that popped up for TSO Life. So phrases and words, and I want you to connect the dots for me. Obviously the resident engagement was there. Software platform, data, analytics. So, bundle that together and tell me how all that works. I would call a typical resident engagement that's a different way of looking at it.  

David Sawyer: A hundred percent is, and that's been our goal from the get go, is we didn't wanna just build another calendar company. Our whole goal was to get to know every resident at an individual level, and then use that insight to look at how do we sustainably and operationally improve their quality of life and quality of experience. 

And to be able to do that, we need to know every resident on an individual level. With our software, one of the things that we start by doing is no paper-based data capture, it's all conversation based where we've built out AI from, I kid you not, training it across over 150,000 interviews that we've done over the past eight years by hand to build out in-house algorithms, to be able to data mine an unstructured conversation and to create those digital resident profiles. And then once we have that great data on the residents, we can then look at things like friend matching, who could your new friend be? We would then look at things at their quality of life score and go, how do we now operationally improve that quality of life score? 

Where are they lacking things and how do we fulfill it? And the great example I gave for this all the time too is, we have a resident that has a physical impairment that they need to get more physically active. They're having falls, having stability issues, knowing that they love chair yoga would be super important for us to then know how to build that into the calendar. We could have chai chi, we could have thousand engagement platforms that are exercises for them. But if they don't go to a single thing that isn't chair yoga, then if we don't have that on the calendar, we're failing that resident. And our software is designed to identify those things, raise it up to the community so that they can go out and execute on it.  

Lisa McCracken: I'd like to break it down a little bit the process. So how do you initially capture the data? You talked about it's not the paper pencil, like okay, Mrs. Jones, what do you, when do you like your meals? Or what's your favorite meal or your favorite movie, whatever. Talk to me about that collection process and then I wanna talk about the steps of bringing it to life.  

David Sawyer: It's a simple conversation. It's a staff member. Getting to meet a new friend is how we tell everyone our goal really is for our resident to feel like they have someone that truly wants to know them, that cares about them and is taking the time to really dive into their lifestyle and what we need to do as a community to serve them. And to be able to fulfill that life experience for them. So it really is just a simple conversation. 

The TSO Life mobile app will actually record that conversation. It sends it back to our backend AI that actually data mines that audio, and creates it into structured resident profile. We typically pull over 150 unique data points from just a 20 minute conversation, which is actually close to over 650% more effective than any paper-based methodologies for capturing data.  

Lisa McCracken: When you and I talked earlier, I had asked you this question like, do you ever get pushback from people feel like, oh, they're recording my conversation and. We know that big brothers everywhere, right? Yep. But I'm just curious to know if you get pushback from residents, family members, ever. 

David Sawyer: We do occasionally. So typically two out of every thousand residents will refuse to be interviewed, and a lot of that goes back to is just how it's introduced and how we're trained on it. Yeah. When you go to a resident and say, here's 15 pieces of paper, you can either sit there and fill it out and I'll wait here, or let's just talk about it. 

Everyone would much rather talk about themself. Imagine going to the doctor's office. Yeah. And rather than getting that paper packet of paper, if someone would sit down and take the time to understand what you're going through, rather than have you fill it out on a form then ask you the same questions two minutes later, it would be a much better experience all the way around.  

Lisa McCracken: Do you have a standard set of questions? It's like a script that the staff person follows.  

David Sawyer: We do have some best guidelines for it. Okay. But operators can customize it. We've been doing this for a long time. Our AI's been trained for over 600 unique questions for it to be able to data mine. At this point, we're surprised when someone has a new question we haven't thought of, but we're always happy to train it.  

Lisa McCracken: How do the staff embrace it? Because I think sometimes these solutions are only as good as what the staff are willing to do it or embrace it. So what kind of feedback have you gotten from the community staff that have adopted this? 

David Sawyer: And that's really, I feel very passionate about when it comes to onboarding new software because we see a lot of times in this industry, people buy things and it sits on the shelf. And as long as the tech company's getting paid, they're usually happy for it to just sit there. And we've never had that mindset. 

We actually look at a health score for every individual community.  

Lisa McCracken: Yeah. Talk to, I wanna hear more about that, but go ahead. Yeah. Yeah, that's on my list. You said that earlier.  

David Sawyer: We dive into this all the time and really focus on making sure that everyone is trained well on the software that's supported it. 

And a lot of it is how just we design our software. It's all focused around how can we deliver value, not just for the resident, but for the staff as well. We typically find everyone joins this industry because they meaningfully want to have an impact on the residents that they serve. 

And they can see how our software helps them go from being able to do it for just a handful to now the entire community. And when we talk to life enrichment directors and even EDs in the buildings, the question we always phrase is, how do you know which residents you really need to spend time with to improve that quality of life? 

And they've really never been able to say, and it's always just been well, we're looking at it, we're trying to take care of everyone. But for me, always, if we don't know what to measure, we're always gonna be running blind to an extent. And so our software being able to identify where those opportunity residents are that have those low quality of life scores, and then getting served up on a platter saying: Here's what to now do with them. We're transforming what someone's job is. It's no longer just keeping our residents busy, but to a way I'm now actually elevating what I'm doing. To sustainably improving quality of life. That gets just a whole different level of buy-in. 

Lisa McCracken: So the fact that you have this quality of life score, then how are you reassessing, residents? I am curious to know that piece of it.  

David Sawyer: Yep. So every six months they can do a recheck, an interview. Okay. We know that data changes all the time, just to, hey, what do you enjoying doing? 

What do you wanna do more of? And it's a great, be able to touch point. What we also were able to do was on the resident app, we can have them fill it out. We can also do the surveys for staff and residents satisfaction surveys. We can put 'em in there. So we have an array of ways to get that updated data in our system. 

Lisa McCracken: Tell me how this looks different, or not, for an independent living resident, assisted living and memory care. Is it applicable for all three? Does it look a little different for all three?  

David Sawyer: Yeah, so it is definitely different for all three. Typically, IL and AL are a little bit similar. Okay. 

Sometimes you'll see the IL residents able to engage with the technology. They're giving us this data, we don't need staff to go get it as much. AL definitely requires a bit more staff engagement to be able to consistently get that data update. And then for memory care, typically that's where the family will get involved too. And we can capture that same level of data from the family too.  

Lisa McCracken: Yeah. Talk us through, okay. We talked about data collection. Yep. All right. So you mentioned what, 150 some data points or something like that, that you collect. All right. A lot. What do you do with that? So talk to me through like the practical operation. How do operators put it into practice?  

David Sawyer: Yeah, so a couple ways that are really awesome. So one of the first things that we do is we have an entire data science team that is actually looking at all this great insight, all the engagement of the calendars, and they're actually creating algorithms to be able to customize things. 

Okay. And so some things that I mean by that is, someone could say that they like walking 15 different ways. I like walking, I like hiking, I like skipping, I like strolling. Fundamentally, for apples to apples data to be applicable, we had to make a taxonomy to be able to map all those things to tie back to that same fundamental category of walking. And then we're able to take that walking and then have it go into exercise. So we could even have light exercise. And so you end up having all this great different categorization or attributes to an individual point that all ties together. Now that we have all that, we then actually take all, I kid you not the history, every engagement calendar that's ever been entered into our system. 

We've actually mapped every single event to similar things as well. So we have an entire taxonomy of every event that's ever happened so that we can actually align these things. Very cool. And so then what we can do even further is now actually have AI that sits on top of this and goes, we have all these residents in your community, you have all of these interests, what should the calendar look like to A, make sure that everyone has something to look forward to. But then B, identifying which residents have the lowest quality of life score. Where are they lacking and how can we make sure that we're personalizing those events to make sure that their specific needs are getting on there too? 

So with our algorithms, we're able to look at the entire community overall, but then also focus on the residents that need it the most and make sure we can get them there too. And that's where the quality of life score identifies which residents we need to focus on. And by able to do that, we can actually show sustained improved quality of life scores for an entire population. 

Lisa McCracken: Yeah. That personalization, I think is huge. You've talked before as well about how do you measure engagement? Yep. And something that seems very obvious and simple, but I know it made me go, oh, okay. Like too often we say, okay, we had 26 people show up to art class today and the wood shop group, we've got this many, and you said that there's fault in that. Talk us through your thoughts with that.  

David Sawyer: Yeah. So one of the things that we've always been a big believer on is we wanted to prove out what the ROI was to good engagement. Because historically, if you look at every single department in senior living, they've had KPIs that they can measure against that tie back to financial ROIs. 

And if you look at what engagement has always been, it just. Did presence feel happy? Is it, does it feel like it's a good, engaged community? But it's always been arbitrary, almost. It's never been tied back to levels of data in science. And so what we did with our team of AI scientists is we actually went out and looked at what are other scales that populations are using to measure these type of things that we could copy or attribute and take in for us as well. And we identified the quality of life scale and self-rated health as being great drivers that CMS looks for amongst their insurance groups to see and do population health management and predictive analytics. 

So essentially what we did is adopted those exact same scales into our platform. So we can go to the CMS and say, hey, your population in this senior living community is actually 20% healthier than that rest of the ZIP code, and so we can actually identify and do apples to apples comparisons, which becomes really impactful for value-based care and social determinants of health. And that's what we really wanted to identify with our platform.  

Lisa McCracken: So what is your role in that? Is that information that you feed to the provider, the operator as additional demonstration of the benefit that they're providing to the communities to then go and have the seat at the table with the payers or whoever it might be, is that sort how do you play? What is your role in that, obviously, other than the data collector and aggregator. 

David Sawyer: It's a little more on the sidelines and I would like, so United Healthcare, if you guys are here let's talk or whoever. 

But long story short, right now we do just feed it up to the community.  

Lisa McCracken: It would be great if a United Healthcare would be like, you guys need to have this in there.  

David Sawyer: Hundred percent because we know the SDOHs. Yeah. Because essentially when we think about it, I was in a panel earlier, listening in on it, and they said senior living should have more of a seat at the table. Absolutely. Because right now groups are coming in to just address one SDOH. If you look at senior living, it's addressing every single one of them - transportation to medical appointments, check, dining, check, housing, check, every single one. 

You go down the list and our goal as data collector is to be collecting that data, that engagement and be able to serve up to show how you guys are actually operationalizing improving SDOHs.  

Lisa McCracken: Yeah. Yeah, I think sometimes we definitely do undervalue ourselves. Oh, a hundred percent. And the voice that we have at the table, and we need data desperately as an industry for sure. 

David Sawyer: And if there's one thing tech companies are good at, it's commercializing data. So let us help you guys out with it.  

Lisa McCracken: Okay. So you're good at the data commercializing, but how do you get the data to live and breathe beyond like the life enrichment person? So can you give me examples of how, if I'm like a CNA in the memory care unit or I'm the maintenance worker. Or I'm in the dining room. How does this have life beyond the person that did the interview with the resident and who's creating the activities calendar?  

David Sawyer: A couple different ways that we have it. One, we believe in true integrations with any technology that's out there. 

We want the CNA to be able to have that data. In their EHR. They shouldn't have to download a different app to go look at it somewhere else. That's where great integrations come into play. And I do think as an industry, we've actually made a lot of headway over the last couple of years. Two or three years ago not so much, but we are, we're getting there. Finally, everyone is starting to pick their head up and go we wanna be able to build a better ecosystem to help operators, because if we can show how the stuff all ties together, everyone wins. And that's definitely the right mindset to have. And so our whole goal is that we can deliver that actual insight directly to the person where their job is. 

So if I'm a dining waiter I'm gonna go visit a table, I could get actual insight from TTSO that's being passed directly on to the point of sales software saying, Hey, this resident you're about to serve just shot their personal record in golf this morning. Congratulate them on that awesome round. 

And so that's how you begin to tie all this stuff together, is you serve up those bite size insights to the staff where they're at.  

Lisa McCracken: So that brings me to another question, and I remember asking you this too. So I think, alright, we've got this inventory of all these things that people loved, and let's say I'm a resident and I loved horse racing. 

You probably don't have a horse racing track at the retirement community, so like how do you effectively connect the dots and deepen this engagement without feeling like you need to be the end all be all? And maybe I'm simplifying it from like an activity standpoint, but talk to me about the balance, 'cause you had a really good response when I brought this up a couple weeks ago. 

David Sawyer: And I'm desperately trying to remember that response, but I'll tell you what, I might have a different response all time. But no, but I,  

Lisa McCracken: That's just a practical thing that popped into my head. So yeah because not everybody has, that can be the end all be all, you can only have so many clubs or whatever.  

David Sawyer: Correct. And so that's really a couple things that we really try to do with the software. One with our AI is we're always looking for other ways to provide that engagement. So you mentioned that horse racing. We'd be able to have, Hey, there's this Derby going on this TV channel, and we can direct the staff to it that way, right? 

The staff doesn't necessarily need to go figure this stuff out. How can we serve insight on a silver platter for people? But the other thing that our software really focuses on doing is finding that resident to resident connections to happen as well. How can we take that resident and put them in touch with the other residents that also love horse racing too? 

And create that club out of it. So our whole goal is we recognize that communities staffing is always a concern, right? There's limited time for everyone. How can we empower the residents to take more control over their day every single day, and give them the tools to make every single day the experience that they want? 

That doesn't require the community suddenly reinventing their staffing model.  

Lisa McCracken: Right, because if it requires a lot more staff intensive time, if it’s a distraction with, they don't see value in it, as we know, that can be a challenge. So you are not only collecting this data, enhancing quality of life and so forth for residents, but you're doing some predictive analytics too. And that is a big deal, as in today's world. And that relates, I think, to some of the value-based care stuff too, above and beyond. Hey, we help with quality of life. Talk to us about what you're doing with that.  

David Sawyer: Yeah, a hundred percent. So the quality of life, self-rated health, all those different scales that we have. 

We did an entire regression analysis on taking those quality of life scores and looking at length of stay. And we essentially said we believe that depending on the resident's quality of life…very poor - they'll stay in the community less,  excellent - they'll stay there for longer. And so we took over six years’ worth of data, over 45,000 residents over a six year period and said, is that true? 

And we scatter plotted all of it. And we did see that for every level of improvement of quality of life, a resident would be expected to stay in their community for 85 days longer. That's significant. If they go from a very poor to an excellent, that is an additional year of expected length of stay for that resident. 

And what we did even further said, okay, that data looks great. We put it then through a regression analysis, which we basically said, what is the likelihood of this data on this plot just being random? And we found that regression analysis was a .00001 percent chance likelihood. That doesn't only show a positive correlation that shows causality. 

Me being the idiot CEO that doesn't know statistics 'cause I slept through that class when I was working on something else, I had to go to my data scientists and say, hey, help me understand that number. And they said that score is the same score that the study that tied smoking to lung cancer had. 

That value was the same as the study that found that wearing a seatbelt could save your life in a car accident. So as society, the way that we say those two things as facts, improving quality of life will extend a length of stay is that same level of fact. And the exciting thing about us, where we can do predictive analytics is now we can actually go look at those very poor residents. 

We make what we call opportunity zone, which is we say, let's focus on them, specifically our AI focuses insights on those specifically. And now as a community, we can operationalize improving length of stay in our community by leveraging resident engagement.  

Lisa McCracken: And that is incredibly valuable for those that are making a financial investment. I think everybody wants obviously the ideal quality of life for the residents. Yeah. These deep engagement platforms. But there does sometimes come down to like, all right, how are we paying for this? Who's paying for it? But things like that, that demonstrate the value in terms of length of stay. And if you can start to predict if somebody's declining, they're less likely to be sent out, for a period of time. Do you guys engage with the family at all?  

David Sawyer: We do a little bit. So we have the family app that they engage heavily with, and they're very interactive with that too. I will say it's always a fun part about getting families and  

Lisa McCracken: Yeah. Your interactive comment. I read the nonverbals there. That's funny.  

David Sawyer: A lot of unique ways they like to use software and, they like to have the text blown up to 1,500 and then wonder why the zoom isn't working and we have fun. That's funny.  

Lisa McCracken: So one of the things I would observe too, with you talking too, you've been doing the AI stuff for a long time. 

David Sawyer: Long, long time.  

Lisa McCracken: Yeah. And it's it seems to be a much deeper thing than sometimes the AI noise you hear out there, which is just chat GPT with a little bit of a, wrap on it.  

David Sawyer: Yep. So we built our own custom algorithms on Python. We literally did it the hard way. 

And so typically with AI, you have to train it. You either have positive reinforcement, supervised learning. So we literally did a lot of the stuff by hand to then have it model it after. And then every single response that the AI would have, it goes through a human qualification check as well. So nothing that leaves our site even today, is going directly from AI to staff.bIt always goes through a human check.  

And so what we saw with that is you need to have the data for the AI to be trained. Otherwise it's just guessing. We're absolutely coming up with bs. And that's one of the things that we see a lot in this industry is there's a lot of companies that are coming out with AI really quickly, almost a little too quickly, and then you almost sit there and going, I've never even heard of this company before. Yet they're saying they have this AI for it, and then the question goes back to how was that trained? What data did you use to train it? And most of the time what it truly is, it's just a ChatGPT extension that they white labeled and said, hey, it's now trained to do this. 

But that ChatGPT wasn't trained on senior living data. It didn't have the right protocols in place to make sure that it's not doing harm. And so that's one of the things that we see is great for the technology for the industry, that new technology's trying to come into it. But at the same time, a little bit of a hesitancy to realize that this stuff takes a long time, right? It's really difficult to do.  

Our friends over at Safely You, they didn't make their fall detection software overnight. They literally looked at hundreds and thousands of falls and went, yes, no, yes, no. To train that algorithm over time and then to detect the step patterns that then led to a fall to be predictive. 

And this stuff really does not just happen overnight. This is really advanced work. Every time I hear someone talk about their new AI, the question I always ask is, who manually trained it? How long did they spend? And if I don't hear thousands of hours and I don't see the battle of war in their eyes of how much of a pain it was, you kinda know they got some vaporware there. 

Lisa McCracken: Okay, so you've been at this 11 and a half years. The organizations that are most successful at integrating this and adopting this, what are some common characteristics that you see, how do they ready themselves to be in an optimal position to really optimize what you're offering? 

David Sawyer: Yeah, so I think a couple things that's really important. One, they have to, even at the very highest end of the company, understand that engagement leads to ROI. That what we're doing with quality of life is gonna have a meaningful impact across the board and that needs to be a strategy for them. 

When we see operators that this technology wouldn't be a fit for, and I'll be the first to tell them, we've turned down people where they come to us and said, I just want a calendar. Here's five other companies that would be a better fit for you, right? If you're not viewing this as I'm going to operationally change the way we think about our resident’s life journey, we're probably not the right software for you. So typically we find operators who are looking for that, who are data driven, who understand that they're wanting to extend that length of stay and have that ye need. And this is the technology that we can operationalize for you.  

Lisa McCracken: I appreciate hearing that because I think it's so important to have alignment with expectations, what you can deliver. And obviously you take pride in what you offer. What's next? Is there, are there any exciting things on the horizon? Anything for the next year or two that more growth evolution. What can we expect?  

David Sawyer: Oh, a whole lot. So we did, as we talked about earlier, just finished raising our series B funding. 

So we got a fresh $43 million and we're putting that to work. We're up to 35 engineers now. We’ve got five in our data science team and our AI team. We are consistently building, building. As a company, our mantra has always been we wanna build the best product and the best experience, and the sales will come after the fact. 

We actually only have two salespeople. Really with the sole mantra of, we'd much rather be building a great product, a great company, and then have the sales come to us, as opposed to having two engineers and 35 salespeople and just trying to sell whatever we can to anyone. And so one of the big integrations that we have that's coming out that we're really excited about is actually engagement on demand. 

So what it is, it's the ability for a resident to wake up and say, today I wanna play Bridge. And our AI system understands all of the other residents that wanna play bridge. It dms them asking if they would like to play today at two o'clock. Oh, I love that. Get a quorum, schedule that event in real time. 

Notify all the residents and have them then go have that bridge event. So our entire goal is how do we make it so any resident can wake up and have the day that they want without the staff needing to go out and make that happen. I love it. Popup bridge party a hundred percent. Our whole goal is going from the TV model to the Netflix model. 

If I wanted to watch my Real Housewives of the Beverly Hills, I need to wait till Tuesday at eight o'clock. Now there's Peacock and I can go on there and watch one of them yell at another one and say something clever.  

Lisa McCracken: Yes. To me that shows evolution and what worked 11 years ago, I'm sure when you started the company. It's a different environment now, so a hundred percent.  

Thank you so much, David. And best of luck to TSO Life. We know you've had great success and we look forward to continued success. And I know your team's here at NIC, the NIC Fall conference, so thank you to all of you listening to us at the 2025 NIC Fall Conference in Austin.