Giri Devanur (03:39):

You will see that real estate transactions still happening on wet signatures and wiring money or like cashier’s check and things like that. So from literally identification on property, till closing and managing the property, et cetera, every step of the way technology is like maybe 15 years behind or sometimes even 20 years behind. One of the funny things I keep hearing from my colleagues in this industry now, even though I come from tech industry, for us like if somebody says tape, that’s like mainframe days of 1980s and ’90s, right? Even today, in real estate industry, the standard term is data tape. What is data tape? It starts there, right? It starts with the recording of the transaction to everything. So everything is like 15, 20 years behind.

Robert Leonard (04:33):

As a technologist and a business guy you must see just the lack of technology in this industry as a huge opportunity.

Giri Devanur (04:41):

Absolutely. Literally every area that I look at is at least 10 years behind. So like everything we can jump to today and then leverage tomorrow’s technology. So I see massive opportunities in every step of the way.

Robert Leonard (04:57):

What brought it on your radar? How did you realize that there was a disconnection between technology that’s available in the real estate industry and the real estate industry, and what are you doing to close that gap?

Giri Devanur (05:10):

My entry into real estate part in the US was a slightly accidental one. I had taken one company to NASDAQ. And after that was trying to figure out what next as my big opportunity. And one of my friend called me saying that she was trying to buy a Airbnb property that was some $400,000. And she had to put $100,000 as a down payment because banks expect 25% down if it is a short term rental. And she said like, “Hey like I don’t have a hundred K, can you solve this problem?” And that is the origin of I getting in more in this space. And like we created wealth around it. How do analyze the property? How do you buy the property? How do you manage the property? That entire life cycle of property management, from property identification to the end goal. I see that like there are technology gaps that we can bridge. That’s what we are working on in ReAlpha

Robert Leonard (06:07):

AI and machine learning, I would kind of classify those as buzzwords. So explain to us what exactly those mean. For somebody who’s not in technology, explain to us simply what AI and machine learning are? And then also explain to us how those work in the context of real estate investing.

Giri Devanur (06:24):

So I know like AI and machine learning, over the last, maybe 10 years have really taken off. Even though like almost 30 years back everybody thought AI will take over and things like that. So, now it has come a long way because of the computing power that has improved. But truly at a very layman terms, AI is how do analyze large quantities of data, right? So like how do you create intelligence out of it? And then machine learning is how do you train the machine in such a way that it can do much better? See, you and I, humans, we have human constraints. For example, we can’t work 24/7. We can’t analyze large volumes of data. We get fatigued and stuff like that. A machine doesn’t have to right?

Giri Devanur (07:11):

So if you train the machine, well, if you give it the right models, it can move at like a hundred X thousand X fast. For example, you and I, if we have to analyze at an individual level, maybe one property and R two properties and R we can analyze. But can we analyze 10,000 properties or 50,000 properties, 100,000 properties, there is no way. AI and ML will help in those kind of analysis. And that is just the beginning of it, right? There are two kinds of data. Structured data and unstructured data. Probably structured data is fairly easier to analyze, but the moment you throw in an unstructured data… For example, we still believe that AI hasn’t really reached its peak. How do you analyze the neighborhood? See, like if you want to buy a house, what do you do? Take a look at the pictures, et cetera, et.

Giri Devanur (08:00):

And the next thing that you do is drive around the neighborhood to see whether that matches your expectation. From the exterior, how does it look like from a human eye? These things are still in the early stages of the technology. Machine learning is being trained to analyze the right kind of property, pictures, is the kitchen really nice or not? A human eye can analyze it much better than a computer, but the more we train the computer, it gets better and better. And eventually it’ll do a much better job than the humans themselves. And it has happened in every other field.

Giri Devanur (08:33):

For example, chess. It’s been already about 10, 15 years that computer defeated a human. And now like Google built AlphaGo, that defeated a human in Go. Go is supposed to be the most complex game. Right? So, the technology is making significant advances, and then we can take all those into this world’s largest business opportunity, right? I mean, I read somewhere that the global real estate value is $370 trillion or something like that. Much of asset class, how do you analyze? Obviously new AI and ML will be the way to go forward.

Robert Leonard (09:16):

Do you consider a lot of the real estate data to be unstructured? I know when I try to look up data, not only is there no laws, is there no common laws across states. For the most part, every state has their own laws. They have their own regulations, their own forms. And it’s the same with data. If you try to find data on a city or a neighborhood or a county, they way you do it for one city, neighborhood, county in one state is different than you do it for another. And so, for me, it can make it super hard as a human, even to analyze the data. So are you running into that issue with AI, and is that considered unstructured data?

Giri Devanur (09:48):

Actually, your question has two parts to it, right? How unconnected these pieces of data. Even though everybody says MLS, right? But, MLS is not one MLS in this country. There are 560, I think, odd MLS databases. Every state has multiple MLS’, the larger the city, there are multiple MLS’ and so on. Imagine 560 odd MLS’ around the country. They’re not connected to each other. They don’t talk to each other and so on. That’s one part of the problem.

Giri Devanur (10:17):

Second part, as you were saying, we have federal laws, state laws, county laws, city laws, and even in even city, between zip code to zip code, half the zip code will be zoning perspective is commercial, some are random mixed in. And unfortunately none of these data is centralized, easy to access. And every little county has its own form, its own way of doing things. And majority of them are non-structured or there is no standardization of forms that you need to fill. Some are like bilingual, I mean, whatever complexity you can think is there in the real estate field, in any field. Probably the only other industry which is as complex as this is healthcare.

Robert Leonard (11:01):

If you could even find it, if you can even find that data [crosstalk 00:11:05] Yeah. Like I can’t find it. You mentioned zoning. I was actually looking for some zoning information the other day for a property that I was looking at buying, not only was it hard to find, but I was eventually able to find it took me forever. And then once I found it, I could barely read it. I think they scanned in like an old document that they wrote on paper. And it was just so hard to read. I’m like, there just has to be a better way for this.

Giri Devanur (11:25):

For real. I know, like we trained over algorithms and built our AI, et cetera. We have analyzed some 128,000 as of today, imagine analyzing 180,000 properties. It’s just insane.

Robert Leonard (11:39):

That AI, that you’ve formulated, I know it’s proprietary. So don’t give us your special formula. But just give us an idea what metrics or characteristics of properties and neighborhoods and cities that you’re looking at when you do this analysis, and where is it getting its data.

Giri Devanur (11:55):

So, we have built our AI from the variety of factors. We use 25 and another 328 elements to decide whether we should buy a property or not. And that starts there, right? The things like how is the neighborhood? Is it close to a good school district? How far is it from attractions and so on and so forth. For us, our criteria is, it is the property Airbnb viable. That’s the market that we are in. And we collect data from multiple sources, multiple ways, we collect it. We leverage machine learning to train every time when we analyze. And most of the times we reject a property. When we reject a property, we help our machine learning to learn that why we rejected. So next time like if a similar kind of property comes, it rejects automatically.

Giri Devanur (12:41):

Right now, we have already come down to maybe almost on a lighter note, like a Ivy league elimination process, right? 6% is the Harvard acceptance rate. How do you bring that? So it’s like a large funnel and comes down. And then we pick only certain properties. And then we built another app called Human. In our case, what we have done is our AI doesn’t help you to make the decision. It helps you to eliminate the properties that you don’t want. Then we built an app called Human Intelligence as an add on to the artificial intelligence. Because we still believe that human intelligence is very critical in making the right decision. Because, nobody can claim that AI has figured it out. If somebody is telling you that they’re not a techie, non techies can tell stuff, but I’m a techie. If I tell something I let to talk to my techy friends. They’ll laugh at me if I say that AI has figured it out. AI can help you to recommend. Yeah, I can help you to reduce the human analysis, but eventually you need the human analysis.

Robert Leonard (13:42):

So where is that human in the loop right now?

Giri Devanur (13:45):

So like say there are 100 properties, right? We analyze 90 of them and then eliminate it. And then rest of the 10 goes through the level of one more filtering that we do. And then we have built an app wherein gig economy workers from around the world can look at some of the images and stuff like that, where yeah. I cannot easily rank those images. And that is where the human picture comes in. And then we take both the scores. AI generated score as well as a human score and we create a hybrid and then that becomes our score. And then final decision it’ll be like maybe three or four or five of them is what humans will analyze.

Robert Leonard (14:29):

Is the AI and models flexible to change as new things change? So let’s just say prior to, COVID more people like to live in a city than like to, as soon as COVID hit, right? So you might have different metrics saying that a city is a great population, especially with Airbnb. I know that drivable destinations for Airbnb did really well when COVID hit, but a lot of destinations that you have to fly to didn’t necessarily do as well during when COVID first hit. So there’s some of these things that could change, and maybe it’s not a global pandemic. Maybe it’s just a trend that comes up and people want to live in the suburbs or they want to go back to the city, or whatever the case is they want to live in the mountains. Can AI be flexible to know what’s important at the time as it’s changing?

Giri Devanur (15:10):

Yeah. Machine learning is pretty much like training a child to talk. If you tell train the child to use a certain kind of words and then the child learns and picks it up, right? Same way, if we give our machine learning algorithms the right kind of training models, it can pick up and then automatically the next time a similar kind of situation or slightly different situation comes, it is… Again every day AI and ML is developing, newer models are coming, newer methods are coming. The more we feed the data the right quality of data and so on and so forth, the AI will be able to detect the kind of changes. And obviously there has to be some human input into that, changing the direction a little bit. But eventually it’ll become smart enough that it is almost like self-driving cars kind of situation.

Robert Leonard (16:03):

There was a small real estate company called Zillow recently that very publicly had a big failure leveraging some sort of AI or machine learning technology to do their iBuyer program. If a company such as Zillow isn’t able to do it. And I know they’re doing a different model, right? They’re doing iBuying, they’re doing flipping and you guys are on Airbnb space. But what makes you confident that you and your team can pull it off with AI and machine learning, when a company like Zillow, wasn’t able to?

Giri Devanur (16:31):

Again, Zillow has done an amazing job. So I don’t want to criticize or anything like that. I’m very respectful of what they’ve achieved and how they’ve built a great company. The challenges of iBuyer were not just technology. There were global headwinds from a supply chain and logistics and human labor issues. And labor market is super hot, et cetera, et cetera. There were multiple issues use that. But one specific thing that we had anticipated one year in advance was don’t make the buy decision based on the algorithm, use it to reduce the number of decisions that you are going to make. And then we had already anticipated that human intelligence is necessary and we built this human app, hopefully that is the different that as we evolve to the next day. Again there are lots of intricacies. It’s not, oh like one thing went right or wrong kind of thing. It’s a combination of things that help make a better decision. And AI can be a decision support system rather than a decision system.

Robert Leonard (17:32):

In the stock market, there has been flash crashes like black Monday, and that was similar to AI or machine learning. Some sort of algorithmic trading failed and caused a massive crash. I know you’ve mentioned that there is human intelligence involved as well. And it sounds like it’s just filtering it down for humans to basically have a better pool of properties to analyze. But do you think there’s a possibility where something like a flash crash could happen in the real estate industry from AI and machine learning?

Giri Devanur (18:01):

I doubt. Because see, if you look at all these iBuyer programs and all the large buyers that are buying properties, if you look at it, it is still a small drop in the big ocean. US real estate is so big that even the largest player today, of single family residences is a company called Invitation Homes, they are still like maybe 88,000 homes or something like. But 14 million transactions happen on a year bases. I mean it’s still very small. I don’t think it has reached a stage where… But if you look at the stock market, algorithmic trading,% where machine learning and AI does the trading, that’s like 45, 50% now. And it is increasing very rapidly and very soon it’ll all be like systems which are dry.

Giri Devanur (18:50):

That is what led to crashes that happened, and flash crash and et cetera. Because, of the algorithm nature of financial transactions. Luckily what has happened in that side, SCC and like NASDAQ and all the computerized trading, et cetera, I come from the financial services trading side. So being involved in, ,and very deeply about those algorithms. So they’re like ahead of the technology curve in some cases. But real estate, as I told you, it’s 15, 20 years behind. Just to come to the current, maybe say 20% or 30% of the real estate transactions are happening through technology. We are years away from that.

Robert Leonard (19:28):

You mentioned a little bit of ago that you got into the short term rentals, which is Airbnb, VRBO, things like that, because your friend was looking to buy one. She didn’t have 25% to put down. There are 10% down programs. You can buy vacation homes. And I mean, there’s so many other ways you could buy real estate other than just short term rentals. So, what is the overarching thesis or idea on why you chose short term rentals?

Giri Devanur (19:54):

See, Airbnb is operational in 220 countries, right? It’s a massive opportunity. Airbnb is already worth $100 billion now. They’re growing rapidly, and they’re consolidating in every market. So we wanted a global opportunity, which is growing and there is circular transformation from hotels to staying in homes. And COVID simply exhilarated that whole process that if you are a family… Let’s say, if you’re a family or friends of six people. If you want to go and stay in a hotel, you’d like to book at least three rooms, right? The cost of the three rooms versus one house with three bedrooms. I mean, simple math tells you that Airbnb is going to be cheaper and better because it has a kitchen. You can make something and eat and et cetera, et cetera. Especially if you have kids and so on, everything changes. What we are seeing is this trend is not limited to US, across the world. So we believe that that opportunity will give us mega opportunity to grow with that rising tide. That’s why we picked short term rentals.

Robert Leonard (20:59):

Are you focused specifically on short term rentals or Airbnb? Do you have platform risk from Airbnb?

Giri Devanur (21:07):

Right now we are only on Airbnb because we believe that they are dominating the market. They are about 40 odd percent in market share. And they are the leader, right? Any technology platform you’ll eventually have a tech monopoly, whether you like it or not. Google for social media, Facebook, and on news, Twitter and on and so forth. We think that may be the way here. So like right now we are in the learning mode, we are a small company. We are doing one platform first, before we go to the other ones.

Robert Leonard (21:38):

How do you think of potential recessions and the impact that could have on short term rentals? And then as a second order effect on your business?

Giri Devanur (21:47):

I am not sure whether there is going to be a recession recession. Like what we saw in the 2008 or 2000, et cetera. The primary reason is the Fed. Fed has done so much of money into the market in the last 20 months. I saw somewhere in some magazine that G20 countries printed 40% more money than ever. Imagine what will happen with that 40% money. That is why inflation is all around. On last Friday, the inflation data came in that US hit seven and a half percent. Highest in 40 years. Are we at the doorstep for a recession? Maybe, may not be. There is a correction around for sure. We have been on a bull market for a long time. So correction is going to happen.

Giri Devanur (22:31):

Is it 5%, 10%? It’s very hard to predict. I’m not an economist, I’m a tech guy. But how we are looking at it from short term rental perspective is if there is a recession, people will become more cautious of spending. At that time they want to find cheaper ways. If you are a family and going on a vacation, or if you’re a corporate team which is going, et cetera. Those are the kind of targets that we are going after. And from a property perspective, we are taking a much longer view, see any recession will not sustain for more than two, three years, right? Eventually it’ll get corrected and comes back. And we are taking a much longer view of 15, 20 year kind of models in our forecasting.

Robert Leonard (23:12):

We talked before about how there just doesn’t seem to be any normal laws and regulations for real estate across states, counties, cities. So with Airbnb, I found that there’s even more laws and regulation. So are you concerned with increasing laws and regulations around short term rentals and how that might impact your business?

Giri Devanur (23:34):

Yeah. See, again Airbnb is one cycle behind things like Uber, right? When Uber started going into cities every city had like medallion owners and they resisted and taxi companies, they resisted that like you shouldn’t be allowing Airbnb and things like that. But eventually right, it got corrected. We believe that the same thing will happen to short term rental industry. There will be some pushback in some cities. And for example, New York City has bunch of restrictions. But outside New York City all the other Burroughs it’s okay. New Jersey is okay. Like that, every area there will be some pockets of resistance, but the rest of the country it’s going to be okay. But the market is so big. Even if we become some 50,000 homes, we are still a small drop in the ocean.

Robert Leonard (24:24):

I want to talk a bit more about your business model. First, how is ReAlpha an investor in every syndicate that goes through the platform? On your website, you mentioned that you get 51% ownership. Do you get that 51% ownership simply for facilitating the deal or is ReAlpha putting money towards required down payment?

Giri Devanur (24:44):

See what we have done is we are doing a Reg A offering, where the investors are investing in the portfolio of all the properties that we are going to buy. Once we buy the property, put it on Airbnb, then we will be offering it to our syndicate members. At that time, the company will be investing 51% in the equity and 49 will come from the syndicate members. So we want 51%. And hence we take 51% of the net revenue.

Robert Leonard (25:09):

We’ve talked about it quite a bit here on the show, but it’s been a while now. And it’s also a little bit of a different context here. So breakdown for us what exactly a syndicate is and how it works with your business model?

Giri Devanur (25:20):

So, the thesis that we started was 60% of Americans don’t have money for a medical emergency. That’s the unfortunate reality of the country, right? So I came to this country with $65. I know how hard it is to figure out how to invest in anything. So first of all, survival itself is difficult. How do you allow people who don’t have access to invest in asset class like short term rentals? That is where we started our journey. And what we have done is with that syndicate member model. So like in every property, there will be four syndicate members for that 49% following a quarter percent. So we have figured out it can be as low as 2,500. Eventually, our long term vision is, can we help it to like… Let’s say you want to own a piece of the short term rental property. Can we help you to come with zero down and then still be able to make? For example, today, for a car leasing, you can go and drive a car out with zero down. Why not for this thing?

Robert Leonard (26:23):

When it gets into the nitty gritty or the tactical part of owning real estate, specifically with your Airbnb properties, who’s actually doing the property management?

Giri Devanur (26:32):

Right now we have partners that we use for property management, because obviously we are not a property management company per se. What we want to do is enable local companies to help us. Right now we have national partners, but eventually we want to work with smaller regional firms who can set up such kind of entities that can be put on the market. That’s what we have done so far.

Robert Leonard (26:56):

What if what are your properties has a loss for a month or two, or even a period of time, who covers that? What if additional money is needed for not just losses, but repairs or maintenance? Are the syndicate partners having to come up with the money or is that covered by ReAlpha? How does that?

Giri Devanur (27:14):

So, for October, six month kind of loss that happens if by chance something goes wrong, it’ll be a reserve fund, which will take care of that. Then like if anything goes beyond that, we have two levels of insurance that covers, if something goes wrong. Water, heater, drinks, or like some flooding happens, because somebody forgot to turn off the water. All those problems will happen. So it can as many situations as possible into our financial model and then built it. But if everything goes wrong… When we designed our system from a buying perspective, there are two elements that we consider. If everything goes wrong, Airbnb yields are not okay. At that time, there are two choices for us. One, to put it on long term rental or sell the property and get out. So we have factored such kind of risk mitigation into our buy process so that we don’t regret later.

Robert Leonard (28:09):

One of the major issues with buying real estate with partners, which is essentially what you’re doing with a syndicate or even investing in equity crowd funding, which utilizes Reg A as well, at least historically, there is a lack of liquidity. Explain how ReAlpha’s model can actually provide liquidity to its investors?

Giri Devanur (28:27):

So for the Reg A investors who are investing now, SCC allows you to go up to one year for that capital raise. We are only three and a half months or something like that into it now. What will happen is once we close the Reg A offering, we can either list on ATS or on a NASDAQ, et cetera. I, with the experience of taking one company to NASDAQ, I think I’m little qualified to do that one more time. Obviously, we can’t predict when we will do that, board will decide when we should list on an exchange. And obviously we have to qualify to be on the NASDAQ. The moment we made criteria for being listed on that, at that time, the management and the board will take a decision to file with the SEC, et cetera. There is a huge set process that we had to do. Alternatively SEC allows that Reg A shares to be traded on ATS. T’s called ATS. Alternative Trading System. So probably we will put on that if we don’t decide on it, national exchange. So that is how the liquidity elements are covered for Reg A investors.

Robert Leonard (29:34):

How does somebody access the ATS markets?

Giri Devanur (29:37):

Oh, it’s a standard process like any other exchange.

Robert Leonard (29:41):

Because they can’t probably access that through their traditional brokerage, right? You’re not going to go into Fidelity and access it.

Giri Devanur (29:47):

Again. It depends on ATS to ATS, I haven’t really studied in depth about each one of them. So it goes by like ATS to ATS. There are some which are really easy and intuitive. Some are like little traditional, but you know, like it won’t be like, oh, you can’t take your Merrill Lynch account and then start rating kind of.

Robert Leonard (30:08):

You mentioned that you had some success and experience with taking a company to NASDAQ. And so throughout that successful career that you’ve had, you’ve raised money a few different ways. But with ReAlpha, you chose to use regulation A. First explain to us in detail what Reg A is, how it came about? And then tell us why you chose this method or strategy to fund your business?

Giri Devanur (30:31):

Very interesting question. I could have raised money to ReAlpha from some private equity or VC firms, et cetera. I chose this time to allow non-accredited investors to being able to invest. What happened was in 2015, the US government allowed, through the Jobs Act, for unaccredited investors to be able to invest in high growth companies that happened in that year and early last year, March of last year. SEC changed the guideline that a tier two companies, the tier one and tier two, there are two kinds of tiers that a company can raise money. Tier one is they increased it to 25 million and tier two is 75 million. So we are in the tier two phase. When a company files for tier two and gets qualified by the SEC it can raise up to 75 million. From both accredited, as well as unaccredited investors.

Giri Devanur (31:23):

The reason why I chose this time was I saw that like any big successful VC backed company, an ordinary investor will not have an opportunity to invest in that money and write that way. It’s just limited to super H people and super HVC firms. I thought like Regulation A gives you an opportunity to democratize this process. Additionally, what we realized was the Regulation A offering investors are also our syndicate members in the future. So, for us, it was a way of building the brand, working with those investors and help them create the new asset class in their portfolio. That is why we chose to use this as a method.

Robert Leonard (32:08):

We’ve talked about it a bit here on the show. So just quickly break down the difference between accredited investors and non-accredited investors?

Giri Devanur (32:15):

I think the latest term is what? Accredited you should have a household net worth of, I think $2 million. You may have to check the numbers. And then you should have at least $300,000 household income. Then you are considered as an accredited investors. Otherwise you are an unaccredited investor. That is the difference.

Robert Leonard (32:36):

And so through your Reg A offering, are you able to raise money from non-accredited investors?

Giri Devanur (32:42):

Yes, non-accredited investors are also allowed to invest up to a certain level. It depends on their annual income, so they can invest up to that in the Reg A offerings.

Robert Leonard (32:53):

Can you clarify for us the difference between your Reg A offering that you’re doing and how you can actually invest in properties, in Airbnb properties through ReAlpha? Explain to us, and explain the distinction there?

Giri Devanur (33:06):

With the Reg A offering, the investors are investing in the company, common shares of the company. That means you are investing in all the properties. Whereas he chose the path to use this so that we can buy a larger portfolio of properties. See with the 75 million, we have a term sheet for a 200 million kind of debt facility, a combo of that, et cetera. Eventually we should be able to buy up to $750 million worth of properties. So like as we go probably a hundred plus properties, we will be able to allow individuals to almost go like a property shopping kind of thing, and then pick in properties and then invest at a property level. We are looking at some new technology solutions for that. We are in the early stages of that discovery. Once that happens in the next few months through our ReAlpha app, which is managed by a broker dealer, we should be in allowing people to invest in individual property. So at that time you are individual property investor. Right now, you are investing in them, all portfolio of ReAlpha.

Robert Leonard (34:09):

We talked a bit earlier about recession and laws and regulations increasing. Well, what other downsides do you see investing in short term rentals, but also what do you see as potential risks for your business?

Giri Devanur (34:23):

I mean macroeconomic issues, if it hits, it hits for everybody, right? It’s not just for short term rental, it is for every other industry. Whether you’re a restaurant, whether you are a movie or anything, every industry gets hit in a recession. So those risks are common for everybody. From ReAlpha specific perspective, obviously like things can be… If our algorithms are wrong or things like, that’s why we are trying to put as many checks and balances so that we don’t make the mistakes that some other companies have done in the past. We are very cognizant of those kind of risks, trying to everyday work on mitigating those risks. Obviously we are a high growth company, fast software driven, et cetera. So we want to make sure that we avoid the mistakes that others are doing, as we make progress. We learn from others.

Robert Leonard (35:12):

Outside of just what you’re working on with ReAlpha, how do you see technology continuing to change the real estate industry?

Giri Devanur (35:20):

The latest trend of buying metaverse and land on decentralize land. Those are the early stages of revolution. Very difficult to say how things will evolve. Right? This reminds me, in 2000, when the internet revolution took off. If you remember the late ’99, 2000, a lot of stuff happened. And a bunch of companies died. But, Amazon got created, Google got created, et cetera. Those companies, eBay and things like that. Those were the companies which rode the way, went public. And then like so stained and grew and grew two of them. Like both Amazon and Google were the product of.com boom. Today they’re multi-trillion dollar kind of companies, right?

Giri Devanur (36:06):

So we are in the early stages of the revolution of the Web 3.0. I mean, that is one of the famous you are hearing everywhere, right? Everybody is talking about crypto and NFTs and Web 3.0 et cetera. We are at the early stage. Companies will figure out new business models, new decentralized ways of doing things. I think real estate is ripe for that, because of the number of transactions that are involved and archaic nature of the documents and all the problems that we discussed in the beginning of this conversation, it is ripe for a disruption. Question is, who is going to lead? Which platform is going to lead? Yet to be decided.

Robert Leonard (36:45):

That’s exactly what I wanted to ask you next. Was, do you see the blockchain and smart contracts kind of replacing… I mean, we mentioned before you still have to sign all your closing documents. I don’t believe there’s any, and if there are, there’s very few that allow you to do DocuSign for your closings. So it’s still going to a closing or getting your documents sent to you and signing them with a paper. And I mean, I’ve done a dozen or more real estate transactions that are two inches thick in documents you have to sign. And I just wonder if there has to be a better way. So I’m wondering if the blockchain and maybe smart contracts, part of that Web 3.0 movement are going to be maybe the solution?

Giri Devanur (37:19):

Absolutely, blockchain and smart contracts are the way to go from, a real estate data and real estate record keeping. Unfortunately, states are still… Again, this comes under the state domain, right? Every state will be different. What if like you are in one state, on Friday, we closed one property and we are observed that one state allowed DocuSign. I was surprised, DocuSign is always considered as a revolution. So the way title industry is literally 10 years behind in technology. And then like all the quarter inch, half inch thick documents and who knows what you’re signing. And what if the pages have changed? Things like that.

Giri Devanur (38:00):

Blockchain and smart contracts will allow transparent, efficient, trusted kind of transactions that happen between buyer and seller. And forget the payments, that’s yet another like massive problem, right? The people even today want check to be written. Wire. Wire is the most inefficient way of any money transaction. Can it be electronic, crypto kind of transaction? I think it is. Time is coming. Now in technology, what we have seen. Initially it’ll happen slowly, but eventually it’ll become fast. We are at somewhere in that curve, towards the end of that slow transition.

Robert Leonard (38:39):

I’ve seen some really interesting blockchain and crypto kind of escrow programs that I think would be really interesting for real estate. But yeah, I buy all of my real estate out of state. I live in the Boston area. All my rentals are in Texas. And every time that I do that, they FedEx me overnight, this probably inch thick documents that I need to sign and I sign 150 pages and I send it back to them. And I just think to myself. Why can’t we just do this electronically? We’d save money. It’d be faster. It’d be probably safer. More efficient. And then you also get a check at closing. You go to the title company and you literally get a check. And it’s like, why can’t we just do some sort of transfer. And I think crypto or blockchain or some sort of Web 3.0 development is going to solve that problem.

Giri Devanur (39:19):

Like notarization, you sit in front of a notary, give a physical license, and then you are to sign on that. Every step can be disrupted.

Robert Leonard (39:31):

Earlier in the show, we talked about how you’re a technologist who is making their way into the real estate industry. And as an entrepreneur myself, I can only imagine that you probably struggle a bit with the shiny object syndrome. We talked about how real estate is so far behind. So as a technologist, you could see all of these different ways or different products or services or ways that you could make money as all these different business models that there are. So how do you personally focus on what’s important?

Giri Devanur (40:01):

So I know what we are looking at is what is a burning problem, right? We are addressing some of the burning problems and we believe that if we are facing the problem and the pain is strong enough, work on it and then solve the technology, rather than everything is shiny, everything is resting right. Then you are like a kid in a candy shop who want everything, right? You don’t want to do that. You want to be healthy, eat the right things. Same way. What we are doing is what are the like critical pain points in this process that is affecting us and then talk to like 20 other, 50 other, 100 other players in the space and see which one need to be addressed.

Robert Leonard (40:39):

Do you do anything specifically to kind of fight off those other ideas that come in? You’ve decided one thing works, you want to work on it, that’s the right idea, but then you still have all these other ideas ping at you. How do you just kind of shoe those off?

Giri Devanur (40:52):

Ah, that’s a hard one by the way. As an entrepreneur and a technologist and seeing so many opportunities, very hard, right? So like what we have done is we have built independent board of directors, really smart people. I’m lucky to say this, that I’ve hired really smart people, smarter than me, in our team. And they become the checks and balances for my enthusiasm. Hey, let’s do this. I say that, but then they say, Hey, that maybe a stupid idea, because nobody wants it yet. And then having a good board helps me to like narrow down, because they tend to ask a lot of questions. And the more the questions are you aim down your enthusiasm and then do the right things.

Robert Leonard (41:36):

I know just that process of being asked questions can be super helpful, because you can be really excited about something. People start asking questions, they start diving in not to change your mind or act like you don’t know what you’re talking about, but just because they’re genuinely curious and you start explaining your answers to them, and then you start thinking to yourself, oh, maybe I don’t actually want to do this. As you’re explaining things, you’re like, oh, maybe they’re right. Maybe this isn’t right, maybe, strategy or product or service for us to go to market with. That’s worked really well for me. People ask me, well, why do you want to do that? And they’ll just dive in a little bit. And when I go to explain that to them, I’m like, oh, maybe I actually don’t want to do this. And I kind of go back to what my original idea was.

Giri Devanur (42:14):

One of the basic aspects of ReAlpha culture that we have designed and harnessed every day is to say that everybody should hire better than themselves. So the more better people that we hire, the rigor of decision making comes. There are smart people and when you have smart people, they’ll ask right kind of questions, which leads to right answer. So it’s about finding that who, then the how part first. That’s where all the transformation happens.

Robert Leonard (42:45):

I know one of the best selling authors, Jim Collins, is really big on that. He has this analogy around buses and he says, “Just get as the right people on the bus. Don’t worry so much about where the bus is going, but get the right people on the bus.” And he’s very adamant about that same strategy as well.

Giri Devanur (43:02):

Good to great.

Robert Leonard (43:03):

Yeah. Good to great. Built to last.

Giri Devanur (43:06):

Built to last. I’ve read both of his books.

Robert Leonard (43:10):

Speaking of books, what would you say has been the most influential book in your life?

Giri Devanur (43:14):

I read a lot of books, at least one a week. That’s been my path for a very long time. The most important book that I read is a book called, Siddhartha. I don’t know if you’ve heard of that. It’s a 1970s book, I think. Very small book. There are three principles in that, you can think, you can wait, you can fast. So thinking, waiting as impatience and fasting, meaning control. Those are the three things which helps you to aiming the monkey mind. Like the Buddhist philosophy is mind is a monkey. It can jump from item to item. Right? How do you tame that? That’s probably one of my best books that I’ve read so far.

Robert Leonard (43:58):

Can you spell that title for us?

Giri Devanur (44:00):

Siddhartha. S-I-D-D-H-A-R-T-H-A.

Robert Leonard (44:08):

All right. Awesome. I haven’t heard of that book, so I’ll be sure to put a list to it.

Giri Devanur (44:11):

Small book. Probably 100 pages or something like that.

Robert Leonard (44:15):

Some of the smallest books are the best books.

Giri Devanur (44:17):

And the other one is the Greatest Salesman.

Robert Leonard (44:22):

Yeah. I’ve heard of that one, but I haven’t read it yet.

Giri Devanur (44:24):

Og Mandino. He was a classic writer.

Robert Leonard (44:27):

Before we give a hand off to where people can find you, I always like to wrap up the show by turning the tables and letting the guest ask me a question. I learned this from a very popular podcaster named Pop. He does this on his shows and I really like it as well. So Giri, what question do you have for me?

Giri Devanur (44:42):

Title of the podcast is Investing 1-0-1 in Real Estate, right? Why 101? Why is it so complex? Why is it not top three or top 10?

Robert Leonard (44:54):

Well, we decided to focus on 101, honestly, it’s mostly because of the size of the audience that we could reach. And so if we were to go with commercial or go to something more complex, you narrow down your audience significantly. And our main business model is growing the shows as big as we can. So we need the biggest audience possible that we can. And so with Real Estate 101, you’re going to have the most beginner investors.

Robert Leonard (45:17):

And so for me, I also felt that when I was getting into real estate, there was a specific resource I wanted that I couldn’t really find. Bigger pockets is great, but I still wanted something a little bit different. And now that I’ve had some success in real estate, now that I’ve grown the show pretty big, I want to help give that back to other people. And I want to be that resource that I kind of wish I had when I was at the very beginning stages. So I really want to help people get that first deal that they have, or first couple deals, second, third deal. Or even if they’ve done a couple deals, but they want to maybe buy their first Airbnb. I want to be that resource that they can go to, go back to class, go back to 101 and learn that new strategy from the beginning. And so I just want to be that resource for people that need it.

Giri Devanur (45:58):

That’s great.

Robert Leonard (46:00):

Well, Giri, I really appreciate you joining me on the show today. I really like your business model and I think it’s really interesting and I can’t wait to continue watching what you guys do. For the audience that’s interested in checking it out, whereas the best place to connect with you?

Giri Devanur (46:15):

Go to realpa.com. That’s our website. And giridevanur.com is my personal website. And LinkedIn, Facebook, Twitter, Giri Devanur. So you can find Giri Devanur in any other social media. But realpha.com is where you’ll find my profile.

Robert Leonard (46:31):

I will put a link to ReAlpha and Giri’s most popular social medias in the show notes as well as the books that we mentioned throughout the episode for anybody that’s interested in checking that all out. Giri, thanks so much for joining me.

Giri Devanur (46:43):

All right. Thank you very much, Robert. I appreciate your time.

Robert Leonard (46:46):

All right guys, that’s all I had for this week’s episode of Real Estate Investing. I’ll see you again next week.

Outro (46:52):

Thank you for listening to TIP. Make sure to subscribe to We Study Billionaires by The Investor’s Podcast Network. Every Wednesday we teach you about Bitcoin, and every Saturday we study billionaires and the financial markets. To access our show notes, transcripts or courses, go to theinvestorspodcast.com. This show is for entertainment purposes only. Before making any decision consult a professional. This show is copyrighted by The Investor’s Podcast Network. Written permission must be granted before syndication or rebroadcasting.