Can AI Fix Housing and Healthcare Affordability?

1. 0:00 – 0:28

   Introduction

   1. MSMinna Song0:00

      We're about 5 million housing units short of what we actually need in the country. Our goal is to enable fully autonomous buildings. An entire portfolio has the ability to run core operations without requiring human intervention at all. Housing and healthcare are the biggest expenses that people have. It's pretty self-evident that technology makes the experience better for everyone and brings down costs, and more people should be working on it.

   2. ETErik Torenberg0:23

      [on-hold music] Alex,

2. 0:28 – 1:55

   Why Housing and Healthcare?

   1. ETErik Torenberg0:28

      we're, we're honored to announce our latest investment in Elise AI. Minna, Tony, welcome to the podcast. Welcome to the portfolio.

   2. MSMinna Song0:34

      Thank you. Excited.

   3. ETErik Torenberg0:36

      Why don't you guys give us, give us a, a brief background or give the audience a, a brief background on, on, on why Elise AI, w-why housing, why healthcare?

   4. MSMinna Song0:43

      We wanted to use AI to solve real-world problems, and housing and healthcare are the bus-biggest expenses that people have. They eat up about 42% of what a typical household makes, and, um, nationally, these sectors make up about 40% of the entire GDP. So it's pretty obvious that we need to figure out how to cut waste in these in-industries. It was pretty crazy to us that not enough people were working on these problems. Top technology people, for example, are not asking the hard questions about, how can we actually fix it? It's just sort of an accepted tax that we all pay. So we started digging a lot deeper into how these systems operate, and once you do that, you can see inefficiencies everywhere you look, and those really add up to huge costs to all of us. And it's also not just about the money, but the quality of these services has a really big impact on people's lives. Um, and when they fail, it doesn't just hurt individuals, it actually hurts kind of society as a whole. So really fundamentally important problem for

3. 1:55 – 3:30

   Technology’s Role in Housing

   1. MSMinna Song1:55

      us to solve.

   2. ETErik Torenberg1:56

      Alex, why-why don't you give the perspective from the, from the growth team in terms of there's been a lot of players in this space over time. What, what got you excited about, about this space and, and, and why this team?

   3. AIAlex Immerman2:06

      Yeah, I mean, as you think about the space, a lot of it ties with what Minna just said, right? So our partner Mark, every year, like clockwork, he sends out this updated chart, and it shows consumer goods and services over time. And if you look at housing and healthcare, as Minna just said, like, prices just go up, up, up to the right, and any industry that technology has touched has gone down. So you can see that in computers, TVs, video games. And we, we keep asking ourselves, like, why hasn't software eaten this industry? Why hasn't software touched housing and healthcare? And right now it's, it's, like, such a paradigm shift with AI where the operational, administrative, and communication b-burden can really change. And so you look at Minna and Tony, like two incredibly tenacious technical co-founders, and they were early to this problem. They started it in 2017, and they have gone deep, first in housing and more recently in healthcare, and the results just speak for themselves. Customers absolutely de-are delighted with the product. You see that qualitatively in the feedback, you know, we heard, but then quantitatively, uh, the scale, the growth, the efficiency, and we're thrilled to partner

4. 3:30 – 5:29

   Housing Affordability & Supply Challenges

   1. AIAlex Immerman3:30

      with them.

   2. ETErik Torenberg3:30

      M-Minna, why don't you go deeper in terms of w-what are the unlocks to actually improve h-housing af-affordability, or why-why don't you give some more context on, on the problem?

   3. MSMinna Song3:38

      Well, for housing affordability, housing supply matters most of all. That's the single greatest determinant of housing prices. So one, we know that we need to, we need to build way more units. We're about 5 million housing units short of what we actually need in the country, and we need to add somewhere between 1.8 to 2 million units per year just to kinda keep that shortage from getting worse, let alone making up for that deficit. We've only developed about 1.5 million units last year, so we actually need to increase our delivery by about 50%. And, um, actually analysts say that the pipeline is shrinking for 2026 and, and beyond. So, um, they said it's gonna drop about, by about 50%, so we're headed in the completely wrong [chuckles] direction. So housing supply matters, but in, in the short term, we can actually get more out of our current supply. So I'll give you an, uh, an example, which is almost half of peop- half of inquiries that go to a rental apartment building never get responded to. So we... You've all experienced this, right? We've all experienced this, that we send a, you know, we, we wanna look at an apartment, but no one... We get ghosted, no one responds to us, and that apartment's still sitting there available, and you want it, but it's being underutilized just because the process is broken. And so, um, if AI is managing all that demand, we can actually turn vacant apartments into occupied way faster, so... And we, we have data that proves that this works, actually, where, uh, earlier this year we provided data to an organization called ALN and found that buildings using our AI had 2% higher occupancy compared to market. So we're, we're working on fixing the affordability problem and the supply problem, um, from a bunch of different angles.

5. 5:29 – 8:13

   Regulatory and Capital Barriers

   1. ETErik Torenberg5:29

      You mentioned we're going in the, in the wrong direction. Can, can you share more about why that's happening and, and what are the sort of biggest, uh, regulatory or technological bo-bottlenecks that, that need to be, uh, a-addressed for that to change?

   2. MSMinna Song5:41

      There's a lot of regulation, um, a lot of zoning laws that cause parts of this problem. Um, but even relaxing regulation will not solve that problem by itself. We also need more capital flowing into housing construction today, and that's a big thing that we think about internally at Elise AI. Capital flows where there are the highest returns, and, um-Right now, housing has lower returns relative to other asset classes. But, um, we're actually enabling housing to achieve higher returns because we're creating these 10X better housing operators that return higher profits to investors. You know, if housing's a stable and, and a higher return investment, how much more capital would be flowing to kind of this, this most fundamental need for society? So, um, you know, that's, that's really great for everyone because it drives more supply into the market, and, and supply is, is really king to fixing the housing crisis.

   3. ETErik Torenberg6:39

      O- on the regulatory side, do you think we'll see full YIMBYism in, in our lifetime? Uh, o- or, or is your view of like, hey, we just gotta... There's some structural reason that impedes that i- in the U.S. relative to so- some, you know, country like Japan, and we just gotta work with what, what we've got.

   4. TSTony Stoyanov6:54

      I think we, we really hope so. Uh, I think different cities actually have kind of started making real progress towards this. Um, Minneapolis is a great example. They, they did a b- big housing reform. Part of that was actually ending single family zoning, uh, rules there, and, and that happened back in t- 2019. And I think ever since that, we've seen like, uh, supplying has grown, uh, three times faster than the national average, and rents have stayed actually flat, uh, for that whole period, uh, compared to everybody else experienced about 31% increase. Uh, so, so I think we're seeing some early signs there, uh, and hopefully other cities and, and, uh, states ta- take that example.

   5. ETErik Torenberg7:39

      And then, I mean, even if we got sort of, you know, uh, Tokyo-level zoning tomorrow, h- h- how fast could supply respond or, or i- is it really just a, this sort of, um, capital, uh, ba- balance that, that is preventing that?

   6. TSTony Stoyanov7:56

      I, I think the data is somewhat clear that obviously it will take a few years to see the full impact, but, uh, I, I, I think if you let people build, um, they will go and build, and, and, and the market will take care of itself. And obviously there will be a lot more innovation as well a- as it gets, uh, much more competitive of a market.

6. 8:13 – 12:50

   Improving Efficiency in Real Estate

   1. ETErik Torenberg8:13

      Why, why don't we go deeper into understanding what, uh, what needs to be true for it to be a more attractive, um, asset class? Maybe you can, you can sort of walk us through it, e- explain a little bit h- h- h- how the d- it's, it's made up and, and what would need to be t- true to improve the, the rate of return there.

   2. MSMinna Song8:29

      It's very inefficient. Uh, that's the reality is that, you know, we're dealing with the physical world, and along the way, real estate has not invested a ton of... in technology, so it hasn't gotten a lot of the efficiencies that, you know, a, a, an internet company or, you know, a SaaS company, um, could achieve. So there's a bunch of headwinds working against this asset class. One is labor. Um, labor is super expensive. Um, it's only getting, you know, it's, it's only getting worse, particularly after COVID. Um, there's a bunch of other reasons like insurance premiums and just costs and supply, uh, supply chain, um, disruptions after COVID as well. But all in all, I think the biggest controllable expense that our customers look at is labor. There's not too much they can do always about, um, or it's not as low-hanging fruit as, as insurance changes.

   3. AIAlex Immerman9:29

      You know, New York, San Fran- and San Francisco are two markets that have really, uh, struggled with housing supply. Assuming we don't get more housing supply in these two cities, what, what do you think can be done to increase the affordability?

   4. TSTony Stoyanov9:44

      Yeah, I mean, I think, um, even if we don't build more units, um, SF vacancy rate is at about three and a half percent today, so there's definitely rooms for, for more efficiency. Uh, you can kind of increase that utilization by, uh, making units turn faster, by filling units faster. Or, or for all of that, you know, better technology can help. Uh, you wanna cut all the manual inefficiencies. Uh, but there are also other ideas around like you can do smaller apartments, share amenities, more flexible layouts. Um, better infrastructure in general also helps. Uh, you know, if you connect Jersey better to New York, obviously that increases the supply in a way in the whole metro area, and that, uh, increases affordability. Um, so, so I think all of these things can help a lot. To a certain extent, those are band-aids. We do need to build more units, uh, and that will be the main way to consistently drive that affordability. But, but I would say there, there's definitely more room for, for improvement even at today's, uh, supply.

   5. AIAlex Immerman10:48

      Yeah. I mean, of course, we hope that more supply gets built, uh, and more red tape gets cut in San Francisco. I know, uh, Eric and I are at least optimistic about Permit SF, uh, led by Mayor Lurie. But I guess, uh, absent that, uh, software probably can be an important lever to resolving some of these issues. Where do you see that tangibly impacting afford- affordability?

   6. MSMinna Song11:15

      I think technology can counter some of the cost inflation and headwinds, but it's, it's also a sector that historically hasn't invested much in tech compared to other industries. So I think number one, we have to execute really well to get these sort of non-tech adopting audiences to use what we build and accept it. Um, but if we do that well, the biggest controllable expense is labor, so AI being used to automate and, uh, and eliminate a lot of the manual and inefficient workflows can help a lot. So we're already seeing customers reduce some of these expenses, and, you know, finding other savings as well, like cutting legal fees because your operations are already more compliant from the start or reducing CapEx costs by optimizing preventative maintenance so things don't break as much. So all of these things add up and, um-You know, if someone's absorbing those costs and, and it's you.

   7. AIAlex Immerman12:15

      [laughs]

   8. MSMinna Song12:16

      So, uh, so yeah, we're creating these sort of 10X operators that-

   9. AIAlex Immerman12:19

      My, my landlord is not thanking me.

   10. MSMinna Song12:22

       [laughs]

   11. AIAlex Immerman12:24

       So we, we've seen, uh, with many of your clients them be able to centralize a lot of their staff, increase AI, uh, as a communication mechanism with their tenants, and the impact has been dramatic. I know with Equity Residential, one of your customers, they've gotten up to 200 units per employee. Maybe just walk us through, like,

7. 12:50 – 18:15

   Automation & The Future of Property Management

   1. AIAlex Immerman12:50

      how do you get from half of that, which I think is like baseline expectation, to, to twice as high, and then how do you think about the efficient frontier? Like, where should that be in five years from now?

   2. MSMinna Song13:03

      Our goal is to enable fully autonomous buildings. So that means an entire portfolio has the ability to run core operations without requiring human intervention at all. So when you look at what actually happens on site at a building, you quickly realize how much of that day-to-day work is just administrative in nature and, um, can be automated away. So really when you're thinking about the physical limits, it's, it's just truly the, the physical work that's left, the maintenance or, um, things that are maybe legally required. So those are the parts that I think are a little bit harder and actually put the, the kind of the, the thresholds on, um, what's possible today. But I think going after full automation is really hard technical challenge that no one has truly figured out yet. Uh, so we really have to sort of reimagine our in- our customers' entire operating models to, to be able to develop products that, that support this. Um, so I think Equity Residential was a great example, really early on had taken advantage of a ton of technology to get cost optimization and efficiencies. Brookfield Properties is another one of our customers. They're building this centralized model that enables a single employee to service multiple properties, and they're actually finding that they can get a single employee to work across 10,000 units using AI in a specialized role. And so think about that, one person managing what used to require dozens of people that were decentralized across multiple properties. It's a, it's a big difference, but you need a huge amount of automation to be able to achieve those numbers.

   3. TSTony Stoyanov14:47

      Even, even the boundaries of what's actually physical are changing fast. Like, I think something like, uh, door access, uh, wasn't a thing 10 years ago, and today we see more and more physical keys are being replaced by smart locks, and now you connect your AI, uh, to, to that system. You can do key provisioning online. Um, and, and we'll see-- I think we'll see more sensors in the buildings, more decisions being driven, and more planning being done by the AI. Of course, there's still some physical boundaries. The AI is not gonna fix the sink, um, but I think we can push that, that boundary quite a lot in the next few years.

   4. AIAlex Immerman15:24

      Why don't you talk through where we are today in terms of what's, what's been automated, what, what's not yet automated, and then we can get to what, what is the, the f- the full vision, and, uh, in that full vision, w-what do humans do?

   5. MSMinna Song15:35

      Yeah, a lot has been automated. I mean, maintenance, you'd have physical boards with covered in Post-it notes with people trying to keep track of what needs to be done. Now that can be automated, um, triaged by AI, prioritized based on urgency of those issues, routed to the right technician, tracked everything automatically, and we see that some operators with this new, these workflows have cut average work order completion times from four to five days down to under 48 hours. So that's really meaningful for residents. Leasing was pretty... was, was maybe one of the worst. It was people just spending entire days answering emails, the same 50 questions over and over and over all day long, and, um, just the same basic information, and now AI can obviously handle that and complete that, uh, those tasks with all of the knowledge of a building or all of the knowledge of a portfolio. Touring was another area of automation, so you'd have to go meet a broker or go meet a, a leasing agent and be physically escorted to every single showing. But now you can... AI can give you access or you can get access through, you know, smart hardware, smart locks, lockboxes, and the AI can still be there to engage and answer all those questions and do the selling. So, um, that gives you a ton of benefits and efficiencies where you're not just having a-- you're paying a whole human just to unlock a single door and, um, actually cuts down average time for our customers from about 30 days from listing an apartment to leasing it to under 14 days because it gives you so much more flexibility to tour around the clock. Documentation was a big area of automation too. Lots of people just copying and pasting fields, uh, just an, an industry that was super ripe for technology [laughs] uh, that just didn't get it for a very long time.

   6. TSTony Stoyanov17:32

      Yeah, and I think this is only even the first order automation we can do. I think there's a whole second order, uh, 'cause all Minna is talking about today is, like, on that single community level, single building. Uh, there's this whole question about, like, how do you kind of organize, uh, the entire ecosystem? How can you share resources, um, whether it's people, parts, tools, uh, between many buildings? Uh, obviously that incle- increases the complexity, uh, b-but for something like maintenance, we, we, we expect to see a lot more dramatic gains once you go on the ecosystem level.

   7. ETErik Torenberg18:11

      And how, how about the second part of the question in terms of, okay, your, your

8. 18:15 – 20:35

   The Human Role in an Automated Future

   1. ETErik Torenberg18:15

      vision comes true in terms of, uh, you know, fully autonomous or fully automated housing. Uh, the-right now there's a lot of people doing a, a lot of those activities or, or, or some of them. What, what do they go do?

   2. MSMinna Song18:26

      I think as AI takes over a lot of the communication and logistics, human roles don't all disappear. Uh, they just-- These sort of AI-enabled career paths start to emerge, and I think you're seeing this in other industries as well. I think expectations are higher. Um, people, like you mentioned earlier, expect that renting an apartment is super easy, super frictionless, and it doesn't require extensive human contact for basic stuff, and that's a great opportunity for AI. So I think you'll see that these career paths are, in the short term, menial parts of the job go away, and people are spending time focusing on building relationships with residents, creating communities. I think people are spending more time at home, right? They're, they're, they're working at home. Their home is their office. Like, you still need this, this human connection, and a lot of our customers we see that are, are creating roles like community engagement and helping people, uh, people socialize. [laughs] Um, I think people will specialize tracks, so you might become, instead of this sort of generalist on site doing everything menial and, uh, and complex, you'll actually see a lot more specialization, and you might become a renewal specialist who handles the trickiest retention cases or a resident experience specialist that resolves conflicts. Um, but I think in the long run, people will be managing big workforces of AI and, um, sort of, uh, overseeing these automated systems that are, are mainly running most of the, the work.

   3. TSTony Stoyanov20:05

      Yeah, and I'll add up to that, that on the maintenance side, uh, obviously I think that physical aspect is never gonna fully go away. I think it'll be a lot more efficient, uh, wh-which I think is really, really needed because, um, on the... Th-there's just huge shortages from, from labor perspective, and a lot of the maintenance technicians today are actually over 50 years old. So you can see that in the next few years it's only gonna get worse and worse, uh, if there's, if there are no more efficiency gains.

   4. ETErik Torenberg20:33

      Go-going back to

9. 20:35 – 21:51

   Financial Engineering & Data Bottlenecks

   1. ETErik Torenberg20:35

      h-how, just the future of, of, of housing for a second. So, um, le-let's say, you know, 10 years from now, we, we have robotics. You know, we've made some major advances in longevity research. Um, we have AGI. [laughs] Um, but, uh, uh, why don't you paint a... What, what's sort of the, the experience go-going to look like, or, or how are those, um, impacts, the, the ones that I, that I mentioned, at least robotics and longevity, going to i-im-impact the, the, the market and asset class?

   2. MSMinna Song21:01

      I think the population is gonna change a lot with AI. Why I kinda talk about longevity is I think a lot of AI research is and, and should be going to m- extending human life. But if, obviously, if you're living longer, there are more people around, staying around longer. And, um, you know, we talk about cost of living a lot. Cost of living is actually one of the... It is the number one reason that people don't have more children. So if AI creates a lot more wealth in the world, and it brings the... and, you know, it, it, it does things like bring the cost of living because of the efficiencies similar to what we work on in housing and healthcare, people have more kids. Again, you have more population. So all these things I think will really affect,

10. 21:51 – 25:33

    The Future of Housing: AI, Robotics, and Mobility

    1. MSMinna Song21:51

       um, will really affect the housing market because all those people, this is a fundamental need for all those people. So, um, yeah, we have to find efficiencies, uh, kinda as I mentioned before. It is more housing supply, and that's where sort of robotics can come in and play a huge role, which is can we use robots, you know, manufacturing? Can we do, you know, modular housing? Can we build faster with robots? Uh, can we bring down the cost of construction? And, um, I actually think this is an incredibly... That's, like, w-that's one area that we've, we've never touched. We're not, we're not a hardware company, uh, yet.

    2. ETErik Torenberg22:31

       [laughs]

    3. MSMinna Song22:31

       But, but it is sort of this big kind of piece of the puzzle in the long-term vision that really needs to be solved by somebody.

    4. TSTony Stoyanov22:37

       And I think you also wanna leverage the technology to increase, uh, mobility in general. I think today people are stuck in these 12-month, 24-month leases. I think you wanna, i-in the future, you wanna have, like, flexibility to just move in tomorrow and that to be very cheap, and, um, you, you c- you can have, like, much, much greater degree of, of flexibility.

    5. MSMinna Song22:59

       Yeah, I think mobility in the market is, uh, incredibly important and productive for society. So if you think about it, if you think about it, we're signing these 12-month leases and locked into these contracts as c- as, as consumers, and that's a, that's a big commitment. A lot of people don't wanna sign these leases, but it's really laborious to turn over every apartment, not just, you know, the maintenance turnover, but, uh, finding somebody, answering all these, you know, the same 50 questions over and over again, touring. It, it's just there's so much labor that it makes it really difficult for an operator, like a housing operator, to find a new, a new resident or a new tenant. AI doesn't really care if it's, it's signing shorter term leases. It's just doing, you know, it's doing that over and over, and it scales. Then you kinda get the benefit for the, f- both for the landlord and for the, the consumer that they can, they can be more, uh, they can do it at, at a cheaper cost, and it, and people can be more mobile. Um, I think that opens up a ton of opportunity that's, you know, people can move for jobs easier. People can move for their, their children's schools. They can increase, improve their quality of life. So I think there's a bunch of different benefits of, of mobility.

    6. ETErik Torenberg24:12

       W-we've been talking about technology as, as a lever here and, and the, the need for it in real estate, and yet real estate spends the least on R&D of, of any other industry.

    7. AIAlex Immerman24:21

       Why is that and what can be done about it?

    8. MSMinna Song24:23

       I, I think solving housing operations is incredibly hard. The search space is massive. There's just a ton of different edge cases. We face this every day. Every single building is different, and, um, it's a, it's a really large expense for people. So it makes all these things make these interactions with an apartment, like leasing, um, it makes these interactions really complex. So in the past, you've really just needed a f- person because traditional software couldn't handle the variability that was required. So if you needed a person anyway, there wasn't really a motivation to buy technology. You just leaned on that person, you leaned on people to do absolutely everything. Of course, those people got really overburdened, but also in the meantime, a lot of that critical data was never collected because it just lived in people's heads. So now AI has changed what's feasible, and it can handle these really large search spaces, uh, it can, it can handle these really complex operations. So in... I mean, in addition,

11. 25:33 – 27:40

    R&D and Technology Adoption in Real Estate

    1. MSMinna Song25:33

       real estate is so far behind on tech, it actually has the most to benefit from AI. So it maybe is going from the lowest R&D spending to potentially one of the highest spenders on AI because AI has sort of finally unlocked automation that was possible that really they couldn't, they couldn't take advantage or they couldn't optimize it before.

    2. AIAlex Immerman25:52

       How do you, how do you respond to critics of PropTech who just say, you know, PropTech is here to help, uh, uh, residential real estate companies extract more value from, from their tenants?

    3. MSMinna Song26:05

       That's honestly a pretty silly argument. I, I get it. I think housing is, is really an emotionally charged subject. People apply these irrational expectations to landlords that they'd never apply to other types of business owners. So think about other industries, like you wouldn't want airlines to stick to paper ticketing processes so that they extract more value... so that they don't extract more value from tech efficiencies, or you wouldn't, you know, if a supermarket didn't use scanners or barcodes. It's, uh, it's pretty self-evident that technology makes the experience better for everyone and brings down costs. So we actually want landlords to use as much technology as possible, um, because, you know, when they're slow to innovate, that's really actually bad for consumers.

    4. TSTony Stoyanov26:54

       Yeah. And we think that the barriers to entry are already quite high. Uh, the operations are very complex. Everything you have to do is multimodal. So much stuff is manual. Uh, so, so I think that limits the amount of people that ca- can get into that business in the first place. Uh, and I think that actually gives a lot more pricing power to the existing landlords. So you can kind of make the argument that actually, like, all of this inefficiency, uh, is really bad for the consumer. And, uh, I think at the end of the day, we believe that competitive markets, you know, take care of themselves. And, uh, I cannot think of a single example where, you know, technology was banned and then costs went down. I th- I think that just never happens.

    5. AIAlex Immerman27:37

       Yeah. It's exa- it's e- it's exactly the opposite, right? So

12. 27:40 – 29:30

    Addressing Criticisms of PropTech

    1. AIAlex Immerman27:40

       generally, when technology is introduced, you see a surplus, and most of that typically goes back to the consumer. The criticism of PropTech would be, is it all going to the property managers and the owner-operators? And, you know, hopefully, as more and more AI is adopted, it's gonna address this affordability crisis.

    2. MSMinna Song28:02

       Yeah, you need mass adoption. That's where the competitive markets take care of themselves.

    3. AIAlex Immerman28:07

       So there's rising repairs, maintenance costs. These keep vacancies, uh, longer. Uh, you know, apartments aren't occupied. This, this leads to higher, uh, housing costs as well. What, what is Elise doing to address this? What can be done over the next five years?

    4. TSTony Stoyanov28:24

       Yeah. I mean, obviously, there's a very physical component that needs to be taken care of, uh, but, but actually where we think AI and technology more broadly can help, uh, all of these problems are actually very complex, uh, planning problems that are quite difficult to solve with, with the current level of technology. There's, um, so much computation that, that you need to do around, like how do you get smarter at scheduling technicians? How do you get smarter at routing? Uh, how, how do you kind of embed a lot of these common sense things that everybody on the ground knows, but y- y- you know, if you're fixing a dishwasher at the same time, somebody can go and fix the holes on the wall. Uh, but if you actually wanna paint the wall, first you need to fix the holes. You cannot just paint over the holes. So, so kind of like there's a lot of technology there that, that we believe we can, uh, build that will make all of these planning, purchasing, scheduling, orchestration decisions so much more efficient. Um, and we're not even touching, like, uh, what we think can be another big, uh, needle around that, uh, preventative aspect

13. 29:30 – 30:49

    Tackling Repairs, Maintenance, and Operations

    1. TSTony Stoyanov29:30

       of like, how do you track, uh, what's going on in a property? How do you know when appliances come near their end of life and, and replace them in, in smart and cheap, cheap ways? Um, and we feel like all of these problems can, can have a really, really big impact 'cause today we see our clients waste, uh, days and days, uh, without... because, like, some piece of information got lost.

    2. MSMinna Song29:57

       Yeah. Every day you shave off from the average unit turn time nationwide unlocks billions of dollars in value. So there's a ton of value just by moving the needle a little bit. The cause of those delays is completely avoidable stuff, so like this part wasn't delivered, or the data wasn't input into the system, so the next person wasn't scheduled for that job, and, uh, it's totally addressable through automation, and those are the problems that, um, I think are really exciting.

    3. AIAlex Immerman30:26

       So when, when I met Minna in 2021, she was-- she and Tony were building a relatively narrow tool for, for leasing. Uh, we were catching up a bit over a year ago in 2024. Leasing had gone to broader residential ops, so maintenance that we've talked a lot about, billing, delinquencies, et cetera. And, and,

14. 30:49 – 33:04

    Expanding from Housing to Healthcare

    1. AIAlex Immerman30:49

       and then she dropped, "We're, we're launching in healthcare. We launched in healthcare." And, and I thought to myself, like, you know, "Minna, Tony, that's insane. Uh, what, what do those two industries have in common?" Uh, and I, I kinda just dismissed it, uh, kept it in the back of my head, uh, and then, you know, catching up a couple months ago, and the healthcare business is humming. Uh, may-maybe share what, what is similar in the workflows, what is different, what's, what's been most exciting there?

    2. TSTony Stoyanov31:21

       Yeah. Um, we've been mostly... Like, I agree with you, like, those two fields look very different, uh, but we've been mostly touching the admin piece of, of the healthcare and, and we found, like, those problem sets are quite similar. You kind of see, like, these very bloated cost structures that, um, you know, have so many inefficiencies. They're all struggling with staffing. All of these total costs, you know, gets pushed to the end consumer. Uh, and, and we, we think a lot of the causes of that is, like, the very similar dynamics we see between these complex digital physicals interactions, uh, th-that are full with regulations. Um, and we believe AI can help qui-quite a lot bo-both of them. We see, we see, like, so much commonality around how they approach things like intake. You have to collect very structured information around names, preferences, budgets, insurances, uh, and you keep dealing with this really high volume of repetitive, uh, inquiries. Uh, you get the same questions again and again and again, um, and it's all done over, over the phone, over conversations. Uh, w-we've been able to, to adopt quite a lot of our technology pretty seamlessly. Uh, we developed our voice technology over the housing space, uh, and that has translated really, really well in the healthcare space. Um, and the same thing with a lot of the scheduling optimizations we've been doing, uh, have translated qu-quite, quite well. So I-- they kind of feel very, very different, but from admin organizational operations perspective, uh, we, we've barely been surprised by anything by transitioning to, to healthcare.

15. 33:04 – 37:46

    Parallels Between Housing and Healthcare

    1. ETErik Torenberg33:04

       We, we spent a, a bunch of time earlier talking about why housing costs are so high. It, it seems like no matter what, healthcare costs remain at a sixth or a fifth of the, of, of, of the economy. Is it that we're just getting a better product for, for, for, for, for, for that cost in our-- because our-- is, uh, healthcare a good that we just keep wanting more of it, and so no matter what, we just, uh, we, we get something be-better and we're just gonna keep spending? Is it, it's inelastic that way? Or is it that some morass of regul-regulatory challenges present-- prevents technology from really, uh, you know, bending that, that, that price curve? Wh-wh-wh-what's happening there? Why are, why are costs staying the same?

    2. TSTony Stoyanov33:43

       I, I, I think it's both are actually true. I, I, I think it's healthcare is definitely a very elastic need where people are getting better healthcare, people are getting more healthcare. I think if costs go down, people would want even more healthcare. So, so, so I, I definitely... And, and that's a good thing, right? I, I, I think that makes people live longer and happier lives, and I think that's super important. And, and that's all true, but I would say, like, on the admin side, uh, I, I don't think we're getting a better admin experience and, and I think the costs on the admin side have really skyrocketed way faster than, than anything on the clinical side. Uh, and I think partially it's people have invested in technology, but it just hasn't been quite good enough, again, because so much is happening, uh, over the phone in these unstructured interactions. Um, but we think with the current level of, of technology, you can actually make a really big dent into the admin aspect.

    3. MSMinna Song34:38

       I don't think in healthcare there's been this huge boom of technology a-adoption that has-- we're, you know, surprised we haven't been, you know, it hasn't flowed to consumers' pockets yet. I think we're-- we'll see that with AI, but I don't think the cycle has given its feedback yet. So I am still hopeful, um, but yeah, it can, I think it can arise in either lower costs or better, better outcomes or, or a combination of both of those things.

    4. AIAlex Immerman35:10

       In, uh, housing, you guys have really gone from leasing to broader resident ops. You've started with scheduling on the healthcare side. Where do you think the platform goes from here?

    5. TSTony Stoyanov35:24

       We, we think for us, healthcare is much earlier. We, we think, we think there's so much more that, that's happening on the admin backend side of things that, uh, w-we feel like there's, uh, so much inefficiencies that, like, needs to be addressed, and I, I think that's gonna take, uh, a, a bit to, to actually cover all of that ground. But I think anything from, um, y-you know, that first interaction to, to the billing cycle and, and more importantly towards, like, uh, how, how do you kind of keep the communication post-appointment, uh, with the patient? 'Cause I think today, you know, you go in, spend ten minutes with the doctor. They, they're definitely very helpful, uh, but then you get a piece of paper and it's like good luck from there onwards. I, I, I think, uh, AI can help quite a lot with, uh, engagement on, on the patient side. And, and I think there's a lot, a lot to be done there.

    6. AIAlex Immerman36:19

       Yeah. You go home from your appointment, you have like four things that you're supposed to do every night for the next week, and what is adherence to that? Pretty low, but if you got, you know, an Elise message every night, you'd probably do a better job.

    7. MSMinna Song36:31

       Yeah, I think AI plays a great role in education and leaving, you know, leaving the outcome on the patient. If AI can scale and, and achieve better treatment planned fulfillment, um, that's going to be better for, for everybody. Um, it's certainly gonna save us a lot of costs. Uh, you know, it's one of the government's largest expenses, and so we're all paying for that, uh, tho-those outcomes being poor as well.

    8. TSTony Stoyanov36:59

       Yeah. And, and, and this adherence is, is not easy at all 'cause, like, again, patients are very stressed when they go to a doctor. It, it's not a, uh, easy thing to do, and, uh, I think AI can help them give them more time after the appointment to ask questions. Obviously, there's things like language barriers that AI can help quite a lot with. So, so I think there's all these benefits then that we'll be able to-

    9. ETErik Torenberg37:22

       Yeah, and involve family members who probably weren't able to attend the appointment or the procedure.

    10. MSMinna Song37:28

        Yeah, or you th- you have to think about all your questions right in the moment when you have that time with the doctor, and then if you think of something, you're, you're SOL, [laughs]

    11. TSTony Stoyanov37:36

        [laughs]

    12. MSMinna Song37:37

        If you think of something too late. Um-

    13. ETErik Torenberg37:39

        In this episode, we've been talking about housing. We've been talking about healthcare. These are two extremely, uh, co-complex markets.

16. 37:46 – 39:57

    The Ultimate Vision

    1. ETErik Torenberg37:46

       I'm curious if you can go back in time, um, you know, knowing what you know now, uh, what, what might have you done differently?

    2. MSMinna Song37:52

       I probably would've started with affordable housing, actually. Affordable housing has kind of every problem that the rest of the industry has, um, plus maximal complexity because of all the dense compliance and paperwork, all the require-- additional requirements, and they are the most underserved. Um, they have the biggest administrative drag, and they are also the slowest, some of the slowest adopters. So it just shows that there's this huge, clear opportunity for them to, to take advantage of AI, and it would just-- it just takes longer to get there. So that's, I think, one big thing I would change. We're actually kind of approaching healthcare in a similar way, which is start with what is the most underserved because that's where we can have the largest impact. The most underserved and the most complex 'cause if you sort of solve those problems, then the rest of it is sort of easier downstream.

    3. ETErik Torenberg38:47

       Perhaps let's close on, on, on ki- the ultimate vision for, for EliseAI. Uh, if, if, if, if you achieve everything you're, you're, you're setting out to do, and obviously you've, you've achieved a, a ton to date, w-w-what, what more can you say about w-w-what that looks like at scale?

    4. TSTony Stoyanov39:01

       I think our drive always has been cost reduction. Uh, if at some point-- And, and obviously it's not just one company's effort, but if at some point we get to a place where, like, housing and healthcare are not cost concerns for, for the average person, I, I, I think that'll be, like, amazing.

    5. MSMinna Song39:18

       Yeah, I think if we can take this forty-two percent of what a household spends on housing and healthcare and bring that down to, you know, twenty-something percent, that is, I think, the-- one of the large- most important problems we can solve, and more people should be working on it.

    6. ETErik Torenberg39:38

       That, that's a great note to, to wrap. Minna, Tony, thanks so much for coming on the podcast and being part of the portfolio. [upbeat music]

Episode duration: 40:08