How AI Finds High-Cashflow Investment Properties from 1.5 Million Listings

Austin Childs (00:00)
Yeah, absolutely. I’d actually love to talk about the first property that I ever invested in. ⁓ my personal portfolio is all in co-living rentals. We had this one in the Oakland Hills, beautiful property, a little bit older though, and the electrical system was not ⁓ up to par for what was needed for the usage that was happening in that home. And I traveled a decent bit for work. So I was on a flight to Seattle.

And our breaker at the property ⁓ started sparking. There was an electrical fire. And fortunately, crisis was averted. There was no major property damage because of the systems that I had set in place to handle situations like those. So let me talk about a few of those that really played a role in this incident.

Michelle Tack (02:20)
Hi, welcome everybody. I’m Michelle Tack from Real Estate Pros. We want to welcome our subscribers and those that are new. We’ve got an incredible ⁓ person that I think ⁓ is gonna help ⁓ a numerous ⁓ investors as well as real estate agents. That is Austin Childs. Austin is in technology and has a platform that allows users within their investment profile, within their buy box of what where they want to be, where they want to go, to be able to get to the granular details of finding properties and understanding where they may be across the United States. So it’s an incredible ⁓ opportunity to quickly find properties, understand the filters around those, and do it across ⁓ the continental United States.

Austin, welcome. ⁓ we’re glad you’re here. ⁓ for those of that are not ⁓ maybe familiar with the capabilities and from the technology side of the house, can you give, you know, a overview of really the benefit, ⁓ what you’re doing and what markets you serve, please?

Austin Childs (03:34)
Yeah, absolutely. And first of all, thanks for having me on, Michelle. Really excited to be here today and and to discuss this with you. So yeah, let me talk about a little bit about the platform that we’ve built out. ⁓ we try to empower investors to find deals even in markets like today, where it’s incredibly difficult with rising interest rates, perhaps ⁓ depreciating rent in certain markets. It can be hard to find deals. And so that’s what our platform does is it takes

Nationwide listings across the US helps each investor with their custom thesis, whether they maybe do their own property management or maybe they can reduce capex in a certain way by maintaining the property well. They take that thesis, they drop it into our platform, and we instantly calculate their return profile for every listing in the US right now. So that’s internal rate of return that’s cat ⁓

That’s cap rates, that’s cash on cash returns, full investment profile on all 1.5 million listings in the US. And then that allows them to sort of find the areas in the US. Maybe it is their hometown, maybe it’s a state or two over, maybe it’s across the country where the best deals are given their particular investment strategy. And so our goal is to surface those in a really easy way such that investors can find profitable deals in minutes, not months.

Michelle Tack (05:46)
What I thought it was interesting when we were preparing for this discussion today is your technology background. And as a data ⁓ scientist or as a in the data world, ⁓ I too come from ⁓ my whole career has been in data ⁓ and software. So can you tell us how that’s helping you ⁓ with this now as a you know, a business that is growing and that you want to continue to grow?

Austin Childs (06:13)
Absolutely. I like to think of this company as a confluence of the my three main backgrounds. One is that I’ve been a real estate investor for nearly a decade now, particularly in the code living space. Second, I have a huge data science and engineering background, as that’s how I was classically trained. And so machine learning, AI all comes naturally to me. And third, I’ve been an investment manager for large financial institutions also for nearly a decade, where we’ve deployed

Billions of dollars into various assets and different funds. And so that’s really what we’ve built is we’ve built something that’s real estate oriented, that uses machine learning and AI in order to identify good opportunities, and has a strong financial, institutional, robust profile of each individual asset such that investors can.

thrust the numbers that they’re seeing when they run these calculations. So my background has played a huge role in developing this product. And I hope that it comes to bear and ends up being valuable for investors that end up using this tool.

Michelle Tack (07:18)
I I appreciate that. ⁓ can you give a fairly not too detailed, but an explanation on how your platform, again, for those that may not come from a technology background, is very different than what the consumer may think of AI today, and you know, ⁓ the implementation thereof. Can you discuss that?

Austin Childs (07:46)
Yeah, I think this is a super important distinguishment that you’re bringing up. AI today, very generative, right? And that’s hugely valuable. It can handle a lot of edge cases or what we like to call long tail problems naturally, which is great. But it’s probabilistic, meaning you may enter the same prompt and get drastically different results just based off of how that model works. But you can’t have that in a real estate investment portfolio. I can’t enter the same property.

And end up with two completely different return profiles. So, what we do is we leverage AI on the back end to sort of help us analyze textual data, but then we force it through a deterministic algorithm and financial formulas in order to come up with a single point-in-time estimate of what your return profile is going to be for that property. So rather than the AI being generative and probabilistic on the front end.

We let it do that on the back end to handle those edge cases that I talked about and provide useful, valuable data into our deterministic process that allows investors to have confidence in the results and that they will get consistent results given the same input. So that’s how we like to merge these two worlds of deterministic and probabilistic AI.

Michelle Tack (09:05)
That’s a wonderful answer. ⁓ let me ask you question in terms of running a business today, right, in high tech, but targeted to real estate when there’s a lot of volatility right now, I think we could all agree around real estate. How are you keeping the business running smoothly ⁓ as much as you can operationally? What are the things that it that you’re doing to

To to ensure that happens.

Austin Childs (10:10)
Yeah. So let me address this both from a real estate portfolio perspective as well as from like a SaaS technology company prop tech perspective as well, if you don’t mind. Let me start with the the latter. So from a prop tech perspective, I think hiring is super important. It is at any point in time, but especially in today’s market where there’s a lot lower ⁓ turnover of inventory, there’s fewer investors out in the marketplace that

are using tools like this. There should be more, but there are, you know, a lesser to a lesser extent ⁓ investors active today than there were, say, five, six years ago, right? So the reason that hiring is super important is that we need to keep costs down to match the fact that revenue is has decreased, but we want to keep up with current outputs and continue to produce better and better products, add more and more features and continue to solve investor problems.

So the key way that we do that is being very diverse in our hiring. So we look outside of the US, we look for maybe people that don’t necessarily have a strong background in what we want to bring them on into, but are very eager to learn, are hungry for knowledge, are willing to use the cutting edge tools. Maybe that is an AI, or maybe that’s just standard technology, and that can enhance their productivity and their work. And so that’s huge for us to keep our sort of bottom line numbers steady.

In an environment that may be very difficult for investors to ⁓ latch on to a tool like this, or at least in a more of a bear environment rather than a bull environment, as we like to say in the finance world. Now, from an in ⁓ real estate portfolio perspective, I think this is where tools like ours really come into play because investors are having a hard time finding deals out there. Maybe their local market doesn’t work anymore because

Prices went for, you know, a skyrocket ride in 2020 and 21. And now rates have also gone up. And so there are no affordable deer deals near them. Well, this is where you need to expand your horizon. But how do I do that when there’s 1.5 million properties across the US? How do I analyze all of those properties? That would take me years to do. And that’s where tools like ours come in, where you can quickly analyze, sort, filter.

By all of your investment metrics and criteria. And that can help you narrow down your scope. Maybe I do just need to go a town over from me. Maybe I need to go a county over from where I am, or maybe I need to look in a different state entirely. There are deals out there that are profitable, but you have to start getting creative about not only your investing strategy, but also your investing geography.

Michelle Tack (12:54)
Right. And I think that’s really important because ⁓ you know as well as I do about the bifurcation, particularly in San Francisco. There was a recent New York Times article where ⁓ the it’s it’s fascinating to me, having lived there ⁓ as you do now, that the lower end of the market is actually decreasing, but the higher end of the market they’re paying over two, three, four million dollars because of AI.

And paying, you know, ⁓ engineers two hundred and fifty million dollars a year or scientists. So it’s a real I think it’s an extreme situation potentially, but at the end of the day, it does really speak to, wow, you know, I lived in California for twenty two years. I never knew that in the Bay Area now. Today, today. And that’s where the data really comes in. Can you talk to that a little bit more?

Austin Childs (13:47)
Yeah, absolutely. Data is hugely important because real estate is such like a micro local, hyperlocal investment space, you need to have data that’s being pulled on all sorts of different zip codes such that you can understand that relationship that you just talked about. Maybe it is a better time to start looking at higher priced homes that maybe rent out to a higher profile tenant.

Or maybe it’s more vacation homes that are doing very well and an Airb short-term rental strategy may be doing better at this point in time. Or maybe you can find these gaps in certain environments where studio prices are really high in a particular market. And that allows for a strategy like co-living to come in and say, Hey, there’s this unmet demand in the rental market space where people need a place to stay, but they can’t afford studios. So can I go

Live with a couple other people, rent out a room, which is beneficial not only for the rental renter, but also for the investor. And so there are data points like this that need to be gathered, aggregated, analyzed, and then assessed in sort of a uniform way. And that’s really what we try and do at Property Alpha is bring in high quality data such that you have high quality outputs and can evaluate these different opportunities and different segmentations of the market.

in a very sophisticated way.

Michelle Tack (15:53)
Thank you for that. Every operator of any business, whether it’s technology related to real estate or in real estate or real estate deals, there’s a time and place when something goes south and it’s pretty critical and you had to fix it. Sometimes it’s a deal, sometimes it’s ⁓ an outage, it could be a number of different things. But can you talk about a time when something was going south on you and you had to pivot quickly?

And you either were able to resurrect the situation ⁓ or you were not, but were able to take that and put that in your armor to become a better operator. Can you speak to that?

Austin Childs (16:35)
Yeah, absolutely. I’d actually love to talk about the first property that I ever invested in. ⁓ my personal portfolio is all in co-living rentals. We had this one in the Oakland Hills, beautiful property, a little bit older though, and the electrical system was not ⁓ up to par for what was needed for the usage that was happening in that home. And I traveled a decent bit for work. So I was on a flight to Seattle.

And our breaker at the property ⁓ started sparking. There was an electrical fire. And fortunately, crisis was averted. There was no major property damage because of the systems that I had set in place to handle situations like those. So let me talk about a few of those that really played a role in this incident.

One was we always have a lead tenant at each one of our properties, and they’re there to handle these crisis moments, to handle any issues that come up.

They’re the boots on the ground that really help us deal with these in-person situations such that we can invest from different areas. We can still travel for work or other business and manage these properties at the same time. And so they were able to triage this, triage the situation well. And one of the reasons they could triage well is because we had given them the tools for success. So we already had an electrician set up. We already had a

⁓ list of sort of emergency contacts should a situation arise. And so they were able to quickly look in their phone for that file, find the electrician that they needed to to ⁓ contact, find the emergency numbers for our local area. And it was all solved rather quickly within a couple of hours and the crisis was averted. If we didn’t have those systems in place, that house would have burned down while I was on the plane and it would have been a disaster. So

These are the types of things that you can do to counteract these unforeseen instances that will come up as an investor is have systems to mitigate those things and train either your employees or if you have property managers or even lead tenants in my example on how to leverage those systems correctly.

Michelle Tack (18:46)
You really, you know, you’re talking about SOPs, right? Standard operating procedures. If something goes or something goes well or it goes bad or and you know, I’m I’m glad you talked about that. before we close today, can you talk about the I know that you have a good network.

And you again you have a network of folks that we talked about before we got on today. ⁓ but I thought it was really interesting how you’re utilizing your network. So could you talk about your network and your invest you know, in real estate as well as technology?

Austin Childs (19:20)
Yeah, absolutely. So network and real estate is huge. So we’ll start there. ⁓ first thing I do is I want to see what other people are doing in the real estate investing world. So I love just talking to investors and seeing what sort of like unique ways they’re attacking the real estate market. It’s such a diverse industry that it’s really interesting to find out how people are leveraging creative and different strategies, especially in a difficult environment like today. So that’s a huge one.

Plus, you have all of your service providers, which is a really good segue from real estate to the company, because service providers are huge in both aspects. So having an agent that you trust, having a broker that you can work out creative financing deals with, having a property manager that can handle specific or unique situations such as co-living is hugely valuable for your real estate portfolio. Turns out for our business, those are also valuable because

We’re very symbiotic with other real estate providers. We all want the investor to be able to do more deals. That’s how we all sort of ⁓ benefit and make money in this industry. And so it’s really nice to have those connections because when one person wins, everyone else can win at the same time. The investor wins by getting a profitable deal, we win by providing them that service, the mortgage broker per wins by providing them the loan, so on and so forth. So

That’s really huge in terms of the business as well as those service providers. And the last area of network connections that I’ll mention is just the my background and the that I mentioned earlier in terms of the people that I met along the way, even outside of real estate, have been very advantageous for this business. So I can go and talk to sort of the head of infrastructure at Google or Discord or go talk to

The lead machine learning machine learning engineer at Tesla and get their take on how our technology is working behind the scenes. Can we optimize this more for users and reduce latency? Can we implement a more predictive algorithm for rents or for home price appreciation? And so having this technical network that I can lean on has been very advantageous to the business as well.

Michelle Tack (21:37)
Yeah, what I love about it is you’re expanding the mind. A lot of people, you know, that I speak with, or just in general, think about their network in a very narrow view. Right. ⁓ I had the opportunity to interview a gentleman who ⁓ was a professional water polo player, ⁓ and his wife was ⁓ a ex WNBA player. And he I asked him, and he was very successful, and I use that as a term of revenue, and

California and I asked them what is your network as you define goes it’s ex-athletes. ⁓ about twenty of them. that I that’s my network. So I think we often forget about just what we’re good at and go back to that. ⁓ look you’ve been an incredible a guest with great content. I’m sure there are a number of people that would like to get in contact with you to utilize your platform or maybe they want to invest with you or what have you.

Austin, can you provide ⁓ your contact information for the team here?

Austin Childs (22:41)
Yeah, happy to. So first of all, you can check out our product at propertyalpha.ai. That’s P-R-O-P-E-R-T-Y A-L-P-H-A dot AI. And then you can contact me at [email protected]. And you can find me on socials either @propertyalphaai or if you want to reach me personally, I’m @austinmacai. And that’s on Twitter, X, Instagram, all of those places. Feel free to reach out to me on LinkedIn as well. Happy to connect with any investors and see if we can help them ⁓ continue to add deals to their portfolio.

Michelle Tack (23:22)
We appreciate it. thank you very much for those that are listening and it found value to this content. We have others ⁓ that are available of different content providers and please continue to subscribe. Those who have not subscribed, ⁓ please do at your convenience. again, Austin, good luck in the future.