Senior Living’s Data Reckoning - A Deep Dive

A multimillion-dollar senior living facility can be financed with nothing more than a 30-day-old PDF and a patchwork of systems that were never meant to talk to each other. That’s the tension we pull apart today: luxury buildings on the outside, broken digital infrastructure on the inside, right as the demographic wave makes the stakes impossible to ignore.

We walk through SeniorCRE and the founder’s contrarian claim that senior living doesn’t just need “more software” it needs less fragmentation. When clinical care, staffing, compliance, and accounting live in separate silos, operators spend their days translating data, and investors underwrite deals while flying blind. We use the airline cockpit analogy to show how dangerous it gets when the people doing the work and the people funding the work don’t share the same real-time reality.

Then we get concrete. On the operator side, we talk EHR integration with Epic and Cerner to shrink admissions time, AI that reads messy medication orders to prevent allergy and polypharmacy mistakes, and vision-based wound care tracking that turns photos into objective healing data. On the capital side, we explore real estate due diligence that parses environmental reports in seconds, an acquisition risk scoring engine, negotiation support, plus investor workflows like 1031 exchange planning, entity structuring, and ESG reporting built for auditable transparency.

If you care about senior living technology, skilled nursing facility operations, healthcare AI, or commercial real estate analytics, this one is a deep look at what “single source of truth” really means when billions are on the line.

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Transcript

Old PDFs Fund New Facilities

SPEAKER_00 0:00

Right now, somewhere out there, there is a multimillion dollar real estate deal being signed for a massive senior living facility.

SPEAKER_01 0:09

Oh, absolutely. Probably several of them happening today.

SPEAKER_00 0:12

Right. But here is the wild part. The data actually backing up that massive check. Yeah, it is highly, highly likely to just be a PDF that was printed, you know, 30 days ago.

SPEAKER_01 0:23

Aaron Powell Yeah, pulled from some absolute patchwork of systems that were probably built during the dial-up era.

SPEAKER_00 0:28

Exactly. I mean, it's a striking contrast when you really think about it. You look at the skyline of almost any mid-sized city today, and you see these cranes building these stunning, state-of-the-art senior living communities.

SPEAKER_01 0:40

They look like luxury resorts now.

SPEAKER_00 0:41

Aaron Powell They really do.

SPEAKER_01 0:42

Yeah.

SPEAKER_00 0:42

But the digital infrastructure running them behind the scenes is fundamentally broken.

SPEAKER_01 0:46

Aaron Powell, which is frankly a terrifying reality when you look at the demographic wave we are currently writing.

SPEAKER_00 0:51

Oh, the numbers are staggering. Aaron Powell Right.

SPEAKER_01 0:53

I mean, we were talking about 10,000 Americans turning 65 every single day. You have 78 million baby boomers entering peak senior living age right now.

SPEAKER_00 1:03

Aaron Powell Yeah. And this is projected to be a$610 billion with a B billion dollar industry by 2030.

SPEAKER_01 1:09

Aaron Powell And it is operating with a severe technological handicap.

SPEAKER_00 1:13

So welcome to the deep dive. We have a genuinely fascinating stack of sources today. We're talking commercial scripts, mock interview frameworks, a press release, and some incredibly detailed architectural blueprints.

SPEAKER_01 1:25

Yeah, the blueprints are wild.

SPEAKER_00 1:27

They are. And they're all for this massive new platform launching into the space called Senior CRE. So our mission for this deep dive is to unpack how this single platform is attempting to basically rewire the entire senior living industry from the ground up.

SPEAKER_01 1:42

Which is no small task.

SPEAKER_00 1:44

Not at all. But what immediately caught my attention in these documents is the core thesis from the founder.

SPEAKER_01 1:49

Right, John Hauber.

SPEAKER_00 1:50

Yes, John Hauber. He says something you almost never hear a tech founder say. He argues that senior living actually doesn't have a software problem.

SPEAKER_01 1:57

Yeah, which is a brilliant pivot. I mean, if you are selling a massive software platform, your first instinct is usually to tell the market, hey, you need more of our software. Right.

SPEAKER_00 2:06

Buy my shiny new tool.

Why Fragmentation Breaks Operations

SPEAKER_01 2:07

Exactly. But John Hauber diagnoses a completely different illness here. He says the industry has a fragmentation problem.

SPEAKER_00 2:15

Aaron Powell A fragmentation problem. So what does that actually look like on the ground?

SPEAKER_01 2:19

Well, if you walk into a typical facility today, you'll see the care team documenting patient health in like one totally isolated system. Okay. Then staffing and payroll are running on completely different software. Compliance might literally just be living on a physical clipboard.

SPEAKER_00 2:35

Aaron Powell Or like a chaotic Excel spreadsheet that one person knows how to use.

SPEAKER_01 2:38

Aaron Powell Oh, 100%. And then the financial performance is just locked away in an accounting silo completely separate from all of that.

SPEAKER_00 2:45

Aaron Powell So the operators running these buildings are essentially juggling, what, five or twelve disconnected systems just to keep the lights on?

SPEAKER_01 2:51

Exactly. They are constantly just translating data between software that was never ever designed to talk to each other.

SPEAKER_00 2:59

Aaron Powell That sounds exhausting.

SPEAKER_01 3:00

Aaron Powell It is. And that operational chaos on the ground floor, it has severe consequences for the people at the very top.

SPEAKER_00 3:06

Aaron Powell You mean the capital side?

SPEAKER_01 3:08

Aaron Ross Powell Right. The investors, the real estate investment trusts, the lenders who are actually funding these massive facilities, they don't have access to any of those daily systems.

SPEAKER_00 3:18

Trevor Burrus Because they're siloed.

SPEAKER_01 3:19

Yeah. So they end up making their underwriting and acquisition decisions based on these static retroactive snapshots.

SPEAKER_00 3:27

Aaron Powell I mean, trying to visualize this, it makes me think of an airline trying to fly a massive commercial jet, right?

SPEAKER_01 3:32

Right.

SPEAKER_00 3:33

But the crew is completely isolated from each other.

SPEAKER_01 3:36

Aaron Ross Powell Oh, that's a good way to look at it.

SPEAKER_00 3:37

Yeah, like the pilot, who is basically the daily facility operator, is looking at one radar screen. Then the air traffic controller handling regulatory compliance is looking at a totally different screen. Right. And the airline executives, the Capitol funding the whole flight, they're trying to make strategic decisions by looking at a printed screenshot of the radar from last week.

SPEAKER_01 3:58

Which is insane. How can anyone safely fly that plane when literally no one shares the same reality?

SPEAKER_00 4:04

They can't.

SPEAKER_01 4:04

No, they can't. And that is precisely where the financial damage happens. The breaks in these disconnected systems don't just result in, you know, minor daily inefficiencies for the nursing staff.

SPEAKER_00 4:16

Right, it's bigger than that.

SPEAKER_01 4:17

Much bigger. They manifest as massive, painful surprises for the capital partners. If there is a sudden spike in staff turnover or, say, a sudden drop in clinical care quality, that operational decay won't show up on a financial snapshot until a month later.

One Shared Source Of Truth

SPEAKER_00 4:34

Aaron Powell And by then it's too late. The damage is done and capital has already been deployed completely blindly.

SPEAKER_01 4:39

Exactly.

SPEAKER_00 4:40

Which brings us to the actual architecture of senior CRE. Because they aren't just trying to build, you know, a better dashboard to slap on top these old systems.

SPEAKER_01 4:49

No, they are introducing a completely unified data model.

SPEAKER_00 4:52

Aaron Powell It's a single shared foundation. So operations, real estate transactions, and capital all run on the exact same source of truth.

SPEAKER_01 4:59

Aaron Powell And that structural shift is profound. I mean, it means the data generated by a nurse at a patient's bedside is the exact same data feeding into the real estate investor's portfolio analysis.

SPEAKER_00 5:08

In real time.

SPEAKER_01 5:09

In real time. It removes those translation layers entirely.

SPEAKER_00 5:13

Okay. So to really understand how that shared source of truth functions, we need to look at where the data actually originates. We have to go down to the ground floor of care.

SPEAKER_01 5:23

Right. Which brings us to their operator module.

SPEAKER_00 5:26

And looking at the sheer scale of this module and the blueprints, I'll be honest, it is almost intimidating.

SPEAKER_01 5:32

Yeah, it's massive. The documentation outlines 1,232 distinct features across 65 modules just for the operator side alone.

SPEAKER_00 5:41

So for the operators, wow.

SPEAKER_01 5:43

Yeah, it covers everything imaginable. You've got clinical excellence, safety protocols, specialized dining tracking, environmental services, billing. It is literally designed to be the central nervous system of the facility.

AI Automation Inside The Facility

SPEAKER_00 5:55

Okay, let's drill down into the mechanics of just one of those features just to see how it works in practice. Um, their zero manual entry admissions really stood out to me.

SPEAKER_01 6:03

Oh, that is a game changer.

SPEAKER_00 6:04

Because when a senior is transferred from a hospital to a skilled nursing facility, there is usually this massive paperwork bottleneck.

SPEAKER_01 6:12

Oh, it's notoriously bad.

SPEAKER_00 6:14

But senior CRE has built these pre-configured connectors to major hospital electronic health record systems like Epic and Cerner.

SPEAKER_01 6:23

And the implications of those connectors are massive. Historically, that admission process meant a nurse literally sitting at a desk staring at a faxed hospital discharge packet.

SPEAKER_00 6:34

Aaron Powell A FAX in 2026.

SPEAKER_01 6:36

A fax. And manually retyping the patient's entire medical history, their allergies, their super complex medication lists into the facility's localized software.

SPEAKER_00 6:45

Aaron Powell How long does that normally take?

SPEAKER_01 6:47

Usually about 45 minutes, 45 minutes of pure administrative data entry per patient. And obviously it is a massive vector for human error.

SPEAKER_00 6:54

Aaron Powell Right. But the press release claims that by pulling that political package over automatically, senior CRE drops that admission processing time from 45 minutes down to just 8.5 minutes. Aaron Powell Yeah.

SPEAKER_01 7:05

Achieving a 94% fully automated admission rate.

SPEAKER_00 7:08

Aaron Powell Okay, but I have to push back here for a second. Sure. As someone who honestly gets overwhelmed when my phone just updates its operating system, reading that this platform has 1,232 features sounds like a complete nightmare.

SPEAKER_01 7:19

It does sound like a lot.

SPEAKER_00 7:20

I mean, if I am a nurse who is already working a grueling double shift, the absolute last thing I want to hear is that I have to learn a massive new technology platform. Doesn't introducing this much advanced tech risk completely paralyzing the caregivers with information overload?

SPEAKER_01 7:36

Aaron Powell Well, that is the most common pitfall for health tech generally. But the source data indicates senior CRE is engineered to achieve the exact opposite effect. How so? The whole design philosophy is centered on removing cognitive load from the staff. So instead of giving the nurse more data to analyze, the system analyzes the data for them.

SPEAKER_00 7:56

Oh, I see.

SPEAKER_01 7:56

Take their prescription intake process, for example. They call it PIL, the physician intent, intake, and execution layer.

SPEAKER_00 8:02

Okay, so I'm curious how that actually works on the floor in a real scenario.

SPEAKER_01 8:06

Sure. So imagine a doctor sends over a raw, unstructured order. Maybe it is a messy fax for a blood thinner or even a vaguely worded verbal order. Right. Instead of the nurse spending 20 minutes trying to decipher the doctor's terrible handwriting or their exact intent, the system's AI reads it and structures it automatically. But more importantly, it instantly cross-references that new order against the resident's known allergies, their current list of medications, and standard polypharmacy thresholds.

SPEAKER_00 8:34

Oh wow. So if that new blood thinner conflicts with, say, a heart medication the resident is already taking, the system catches it instantly.

SPEAKER_01 8:42

Exactly. It throws a red flag and halts the process before the nurse even touches the pill bottle. It detects the ambiguity and stops the medication error before it happens.

SPEAKER_00 8:51

So the technology isn't demanding the nurse's attention. It is basically acting as a safety net.

SPEAKER_01 8:57

Aaron Powell Right. It's catching the human errors that inevitably happen during translation.

SPEAKER_00 9:01

That shifts the dynamic entirely. And I noticed a similar mechanism with their advanced wound care system.

SPEAKER_01 9:06

Yes, that's another huge one.

SPEAKER_00 9:08

Aaron Powell Because pressure injuries are a massive problem in senior care. But this system uses AI to analyze photos of a wound taken by the staff, right?

SPEAKER_01 9:16

Aaron Powell Yeah, it automatically calculates the length, width, and depth of the wound and tracks the healing progression over time.

SPEAKER_00 9:22

Aaron Powell And it actually adjusts for lighting and angle, so you get an objective mathematical tracking of the healing process instead of just guessing.

SPEAKER_01 9:31

And the financial impact of that objective tracking is highly quantifiable. I bet. The sources estimate this AI analysis prevents about eight severe stage three or four pressure injuries annually for a typical facility.

SPEAKER_00 9:45

Aaron Powell Eight of them.

SPEAKER_01 9:46

Yeah. And when you factor in the cost of treating those severe injuries, the facility is saving roughly$320,000 a year.

SPEAKER_00 9:54

Just from that one feature.

SPEAKER_01 9:55

Just from that. And when you aggregate all of these operational automations, the admissions, the prescription checks, the wound care, the end result is 520 minutes of administrative time saved per day, facility wide.

SPEAKER_00 10:09

Wait, 520 minutes? That is nearly nine hours of nursing time completely repurposed. Yeah. You are essentially giving a full shift back to actual human patient care every single day.

SPEAKER_01 10:19

Exactly.

SPEAKER_00 10:19

But it isn't just the clinical peer they are optimizing, is it? They are turning this exact same analytical lens on the staff themselves.

SPEAKER_01 10:26

Right, which is fascinating.

SPEAKER_00 10:28

Yeah, the their turnover prediction engine, they call it WRIE. It was honestly one of the most surprising parts of the blueprints for me.

SPEAKER_01 10:34

The workforce retention intelligence engine. Yeah. It uses machine learning to predict which specific employees are at risk of quitting. It flags them 30, 60, or 90 days before they actually hand in their notice.

SPEAKER_00 10:48

Okay. I have to say, when I first read that, my immediate reaction was defense.

SPEAKER_01 10:52

Oh, totally.

SPEAKER_00 10:53

I assumed this was going to be some sort of dystopian Big Brother surveillance tool, you know, like tracking how many minutes a caregiver spends in the break room or logging their keystrokes.

SPEAKER_01 11:04

Aaron Powell Right. But the documentation is incredibly strict about what the model does not do. It explicitly excludes all protected class data. Aaron Powell Okay.

SPEAKER_00 11:12

That's important.

SPEAKER_01 11:12

Yeah. There is absolutely no race, gender, age, or religion data fed into the algorithm at all. And it uses zero invasive surveillance.

SPEAKER_00 11:20

Aaron Powell So then how does it actually predict someone is going to quit if it isn't watching their every move?

SPEAKER_01 11:26

Aaron Powell It analyzes the mathematics of their work environment. It looks for systemic operational friction.

SPEAKER_00 11:31

Aaron Powell Give me an example of that.

SPEAKER_01 11:33

So it asks questions like: Has this nurse had their schedule abruptly changed three times this month? Have they been forced to work six consecutive weekends?

SPEAKER_00 11:40

Oh, I see.

SPEAKER_01 11:41

Or, you know, have they gone two years without a compensation adjustment while local market rates have steadily risen? It basically looks at the subtle compounding factors that lead to schedule burnout.

SPEAKER_00 11:52

So it is identifying the structural reasons people get ground down.

SPEAKER_01 11:56

Exactly. And once it flags a nurse who is at high risk of burning out, it auto-generates intervention recommendations.

SPEAKER_00 12:03

Aaron Powell Like what kind of interventions?

SPEAKER_01 12:05

Well, it might suggest giving them the next weekend off or offering a targeted retention bonus before they even start looking for another job.

SPEAKER_00 12:12

That's incredibly proactive.

SPEAKER_01 12:13

And the blueprints indicate this approach reduces turnover by 15 to 25%, which, when you do the math, saves an estimated$280,000 annually in replacement and onboarding costs.

Due Diligence With Real-Time Data

SPEAKER_00 12:25

Wow. And this actually brings us to the critical transition point of John Hobber's thesis. Because all of this pristine, AI optimized data living on the ground floor, the automated admissions, the exact healing rate of a wound, the real-time stability of the nursing staff, that is the exact same data that flows upward to the people holding the purse strings.

SPEAKER_01 12:48

Right. The capital.

SPEAKER_00 12:50

So if an investor in New York is looking to buy a facility in Ohio, how do they actually interact with that operational reality?

SPEAKER_01 12:57

Well, this is where the buyer module comes in.

SPEAKER_00 12:59

Which has 439 features of its own, by the way.

SPEAKER_01 13:02

Yeah, it is robust. And it seems designed to completely eliminate the blind spots in the acquisition process. Because if you've ever been involved in one, the due diligence process for acquiring a commercial healthcare property is notoriously exhausting.

SPEAKER_00 13:15

I can only imagine.

SPEAKER_01 13:16

Buyers are usually just buried under mountains of risk assessments, but senior CRE has built tools to fundamentally X-ray the real estate deal.

SPEAKER_00 13:23

X-ray the deal. I like that.

SPEAKER_01 13:24

The way they handle phase one environmental site assessments is a perfect illustration of this.

SPEAKER_00 13:29

Oh, I was looking at that in the sources. Usually an investor receives a dense, you know, 200-page PDF from an environmental consultant. Right. And a human being has to sit there and comb through hundreds of pages of soil sample histories and historical zoning jargon just to find out if there used to be like a gas station next door 30 years ago.

SPEAKER_01 13:49

Aaron Powell, which takes forever. But senior SIRE uses Vision AI to parse that massive document in seconds. Seconds. Literally seconds. It automatically extracts the recognized environmental conditions, the RECs pulling out the exact historical risks and the consultants' recommendations instantly.

SPEAKER_00 14:08

That's incredible.

SPEAKER_01 14:09

And then it synthesizes all of that environmental data alongside the real-time financial and operational data and feeds it into an eight-category risk scoring engine.

SPEAKER_00 14:17

So it's looking at everything at once.

SPEAKER_01 14:19

Everything. Financial volatility, regulatory compliance history, physical building age, local market saturation. It aggregates all those complex variables into a single simple risk score of zero to a hundred.

SPEAKER_00 14:32

So the investor is no longer guessing. They aren't relying on gut instinct based on a static report from a month ago.

SPEAKER_01 14:38

No, it changes the entire dynamic of the negotiation table.

SPEAKER_00 14:41

Oh, speaking of the negotiation table, here is where it gets really interesting. They have this AI offer strategist that honestly feels less like a software tool and more like having a quantitative analyst whispering in your ear.

SPEAKER_01 14:55

Yeah, it's a very active partner in the deal.

SPEAKER_00 14:58

It really is. It analyzes the seller's leverage, looking at days on market and past price reductions, and calculates a seller motivation score.

SPEAKER_01 15:06

Which is wild.

SPEAKER_00 15:07

And it will actually predict your win probability for a specific offer price and pre-built counteroffers. It's not just a database, it is an active negotiation partner.

SPEAKER_01 15:17

And you know, once that property is successfully acquired, the data flow doesn't stop. It moves seamlessly into the investor module.

SPEAKER_00 15:23

Which has 198 features.

SPEAKER_01 15:24

Right. And this module is designed to democratize the kind of institutional grade financial tools that previously only multi-billion dollar private equity funds could afford to build.

SPEAKER_00 15:34

I'm trying to picture what those tools look like in practice for, say, a mid-sized investor.

SPEAKER_01 15:40

Well, the 1031 Exchange Planner really highlights the stakes here.

SPEAKER_00 15:43

Okay, so for anyone listening who operates in this space, you know how unforgiving a 1031 exchange can be. It's that tax code provision allowing you to defer massive capital gains taxes when you sell a property, provided you reinvest those proceeds into a new one.

SPEAKER_01 15:59

Right. But the rules are absolute.

SPEAKER_00 16:01

Exactly. For the day you sell your property, you have exactly 45 days to formally identify a replacement property and exactly 180 days to close the deal.

SPEAKER_01 16:10

And if you miss that deadline by a single day, or if you calculate your reinvestment incorrectly, which creates something called boot, which becomes immediately taxable, you are hit with a devastating tax bill.

SPEAKER_00 16:21

It is an incredibly stressful window.

SPEAKER_01 16:23

Very. But the investor module tracks those deadlines automatically. It calculates the boot, tracks the intricate rules, and basically removes the panic of day 44.

SPEAKER_00 16:32

Which is a huge relief. They also include an entity structure manager.

SPEAKER_01 16:36

Yeah. That compares the tax implications of holding the property in an LLC versus an S-corp, a C Corp, or a REIT.

SPEAKER_00 16:42

And the sources claim this optimization alone saves between$250,000 to$500,000 annually for a typical$50 million portfolio.

SPEAKER_01 16:51

It's massive. And we have to look at how they handle ESG reporting too, environmental, social, and governance criteria.

SPEAKER_00 16:58

Right. ESG is huge right now.

SPEAKER_01 16:59

It is. The platform automatically tracks a facility's carbon footprint, its resident satisfaction scores, and its regulatory ethics, compiling an auditable ESG score from zero to 100.

SPEAKER_00 17:11

And why does that specific score matter so much for the capital side?

SPEAKER_01 17:15

Because by automating that transparency, the facility suddenly becomes eligible for a pool of roughly$35 trillion in ESG-focused institutional capital.

SPEAKER_00 17:25

$35 trillion?

Market Validation And Measured Value

SPEAKER_01 17:26

Yeah. Capital that would never ever touch a fragmented opaque operation.

SPEAKER_00 17:30

Aaron Ross Powell Wow. You know, when you step back and look at the sheer scope of this, over 1,400 features bridging the gap between a nurse's schedule on the ground and a multi-million dollar tax strategy at the top, it really begs the question of motive. Well, why take on the entire ecosystem at once? In the mock interview framework, John Harbo explicitly states that their biggest risk isn't moving too slowly. He says the biggest risk is moving too fast and compromising the integrity of that unified data model.

SPEAKER_01 18:01

Which I think reinforces that he isn't just trying to sell software subscriptions as fast as possible. If we connect this to the bigger picture, the ultimate goal of senior CRE is market validation. They are setting out to prove that when capital partners are finally given true, real-time operational visibility, when they can actually see the exact health of the ground floor, their tolerance for surprises will drop to absolute zero.

SPEAKER_00 18:26

Oh, I see. Once the investors realize they don't have to fly blind anymore, they will never accept a 30-day old PDF again.

SPEAKER_01 18:32

Exactly. They will demand operational truth before they write the check.

SPEAKER_00 18:36

And when the capital markets demand that level of transparency as a baseline standard, the old, fragmented way of running these facilities becomes financially unacceptable.

SPEAKER_01 18:46

Right. Senior CRE stops being just another software vendor and becomes the fundamental infrastructure the industry requires just to exist.

SPEAKER_00 18:54

So let's tally up what this infrastructure actually delivers in the end. According to the press release, senior CRE claims an 11-0 competitive advantage against legacy systems like point-click care and YARTI.

SPEAKER_01 19:06

Yeah, they argue that no one else in the market is offering these 11 specific AI innovations unified in a single platform.

SPEAKER_00 19:14

And for a typical 120-bed skilled nursing facility, they quantify the annual value created at$7.06 million.

SPEAKER_01 19:22

And that$7 million figure isn't just an arbitrary marketing number.

SPEAKER_00 19:25

Well, it's very specific.

SPEAKER_01 19:26

It's derived from hard operational math. It is the labor savings from AI optimized scheduling, the massive revenue capture by ensuring Medicare billing is perfectly accurate, the hard dollars saved by reducing staff turnover, and you know, the avoided costs of preventing severe medical errors and pressure injuries.

Alignment And The Bigger Question

SPEAKER_00 19:42

It is honestly a masterclass in applying systems thinking to a broken environment. Which brings us back to you listening right now. Whether you are studying health tech, preparing for a complex real estate acquisition, or you simply love dissecting how massive systems operate, the ultimate takeaway here is about alignment.

SPEAKER_01 20:04

100%.

SPEAKER_00 20:05

True. Industry rattling transformation doesn't come from building a prettier user interface or adding more features to an isolated tool. It comes from building a single source of truth that perfectly aligns the people doing the grueling daily work on the ground with the people funding it from the top.

SPEAKER_01 20:22

Yeah. When the pilot in the cockpit, the air traffic controller in the tower, and the airline executives in the boardroom are finally looking at the exact same real-time radar screen, the entire nature of the flight changes.

SPEAKER_00 20:33

It is a beautiful way to frame it.

SPEAKER_01 20:34

Yeah.

SPEAKER_00 20:34

And that leaves us with a lingering thought to chew on long after we wrap up here today.

SPEAKER_01 20:38

What's that?

SPEAKER_00 20:39

If senior CRE successfully proves that a massive, deeply fragmented, and heavily regulated sector like senior living can be unified into a single infrastructure data model, what other legacy industries are out there right now operating in the exact same chaotic state?

SPEAKER_01 20:56

That's a great question.

SPEAKER_00 20:57

I mean, whether it's education, global agriculture, or maritime logistics, how many other multibillion dollar industries are currently flying blind on disconnected nineteen nineties technology, just waiting for someone to step in and build their true operating system?

SPEAKER_01 21:09

Something to really think about.

SPEAKER_00 21:11

Definitely. Until next time.