Doug Sullinger Podcast Transcript
Doug Sullinger joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to Coruzant Technologies, Home of The Digital Executive podcast.
Do you work in emerging tech? Working on something innovative? Maybe an entrepreneur? Apply to be a guest at www.coruzant.com/brand.
Welcome to The Digital Executive. Today’s guest is Doug Sullinger. Doug Sullinger is the Founder and CEO of Baizel AI, an AI-powered platform focused on improving how commercial real estate site selection decisions are made.
Based in Tampa, Florida, he leads the company’s go-to-market strategy, working with operators in QSR, retail, and healthcare to evaluate and execute location decisions more efficiently. He also serves as Principal of Vendita, where active deal flow across brokerage, operators, and partners provides real-world insight into how site selection decisions are made and where they break down.
This experience directly informs Baizel’s product development and positioning. Doug works centers on helping companies move faster and make more informed expansion decisions in complex high-stakes environments.
Well, good afternoon, Doug. Welcome to the show.
Doug Sullinger: Hi.
Brian Thomas: Nice to meet you, Doug. I appreciate you making the time.
You’re hailing out of Tampa Bay, Florida today. I am in Kansas City, so again, appreciate your time and efforts to traverse time zones and calendars to get here. And Doug, if you don’t mind, I’m gonna jump into your first question. Let’s start with your journey. You spent years at Fortune 500 companies like Oracle, General Motors, and IBM, then built technology ventures in the automotive sector before founding Basil AI.
How did that path lead you to commercial real estate site selection?
Doug Sullinger: Well, thanks for the, the time, Brian. I started my career in Midwest Ohio as a farm boy. Hardworking understood the, understood the value of a hard day’s work. I was supposed to go off and be a farmer when I went to college, and I found software and computers.
And I realized back then that it doesn’t really matter what kind of technologies you’re looking at, technologies are there to improve human processes. And so as I went through college, I quickly switched over to technology world, ended up with a company called Dun & Bradstreet, which a lot of people know.
Moved from there off into some of the largest corporations in the world. At the time, Gardner, which is like a large consumers report for technology picked me up ’cause they were owned by Dun & Bradstreet. And then I got to kinda drink from a fire hose, and that was what, technology on every topic, whether it be networking, software development, app- application development, and I got a really strong understanding of how technology was put together, and then ultimately how it was applied to different business pro- problems.
That then took me into working for IBM, ultimately working with General Motors as the– one of my clients, and at one point in time, I was responsible for all the software that went into those companies. And so, I really understood what the difference was of being a developer and what the business problem was.
I was the guy that sat in the middle. I was never the guy that did the coding. I understood what coders did, but I also tried to understand what the business processes were that people had. So in automotive, the biggest thing that they do is they’re trying to automate supply chain. How do I get my parts into a car as fast as we possibly can?
I worked in that space for a number of years, and then probably almost ten years I worked in that space. Then from there, I found myself realizing that I could be more f- more, have more flexibility as my own entrepreneur, and then that’s where I started Vendita. Vendita then basically was a technology reseller, but we would take technology from some of the biggest companies, and then we would help apply that to different business problems.
That was a very successful company until the– about to- towards the end of COVID, the cloud changed. Everybody talks about cloud computing. And then really, what we were doing is we’re– software is now being held in a cloud, not versus on-prem. And on-premise, this is where you buy it, put it into a server.
That was a journey that kinda got me to where I realized that selling just software itself and trying to implement on-premise software was not really a future for me I saw a place in, in 2022 where I met a really good friend of mine, and she’s now become more than that. She was in commercial real estate.
And so she inter- asked me just to go along for a ride and said, “Hey, let me introduce you to some of my clients.” And I’d seen where technology that I had been in had kind of peaked and gone through a… gone- started going through a lull at the end of COVID. And now we started looking at what was the latest and greatest thing that was gonna change the way people did work.
So, to go back through a bit of a history, if you look at client server, this is where we had a server, a mainframe server, and we all tied into it. Now we dispersed that technology. Then we went into cloud computing. Then we started doing this thing called Internet of Things, where we track everything. Well, the next thing now is AI, and that was about the time in 2022, ’23 is when I recognized that, where, what AI was about to become.
I was just basically had some technology looking for a problem, and that’s really when I met the, met the right person and I got into the commercial real estate space.
Brian Thomas: That’s awesome. I love the backstory. Of course, curiosity drove a lot of what you did. But being raised on a farm, your work ethic is second to none, and I’ve heard a lot of folks that were on my podcast that were- went kind of through that same journey.
So, I, I really appreciate that. But obviously, college led you to the technology, and you were good at. When you got into the business world you understood the business processes. You were able to communicate between the business heads and the technologists, which I think is an amazing skill to have.
But you pivoted along the way, journey to cloud, to IoT, and now you’re in AI, and I think that’s amazing, so thank you. Doug, site selection historically meant weeks of manual research, pulling fragmented data from hundreds of permitting authorities. How does Basil compress that timeline, and what does the workflow look like for a broker or developer using it?
Doug Sullinger: So, let me tell you that in a kind of a story. So, the lovely lady that I met Brandy McAdams, she is the master broker for our, for our brokerage house today. One of… I call her a savant in the business. She understands it better than most anybody. What does it take for an investor in a particular piece of real estate? What does it take for them to actually go, go in and make that decision?
So, they have to look at literally three hundred pieces of data to do that. And a lot of that data is hidden on hidden in public sites or it is buried, behind some kind of data provider. There’s probably at least seven or eight data sources that we pull from, and I’d say between all that, we have about s- about a hundred and seventy, a hundred and eighty different data sites.
And we go out and we purchase that, and then we cleanse that. So, I’m gonna talk a little bit about what that takes to cleanse the data, because it doesn’t matter whether it was any one of the other technologies, everything starts with data. And I don’t care whether you’re talking about with AI, and you still get hallucinations, and you still get…
AI will still fight with you about data and data quality. So, we have started by looking at what data does it take to make that decision. So, if I’m an investor, I’m a developer, I am a broker, and I’m trying to sell a piece of property, what does it take for me to convince an investor to go out and put millions of dollars into this product?
It’s not like a home. Home’s all emotional. When it comes to an investment, it comes down to dollars and cents. Does this piece of property pencil for your particular use? So what the, what a person would have to do is either they had had their own analyst. If I’m an investor, I’d have to have my own analyst team, and they’d have to go out and look at all three hundred pieces of data, no matter where it came from.
Like I said, a government site, it could be it could be is… an Uber site, it could be any kind of a Google site. It could be all types of different sites that they’re looking at, and it would literally take them weeks to months to actually be able to decide, “Do I want to invest in this piece of property?”
So, what we did, what we did was we took Baizel and we said, “Let’s put all of this together and put it into a, a high quality data set.” And I use an example here in Tampa, there is Tampa General. In public s- public records, they call that a hospital. If I go over to Orlando, they call it a medical center. So what we have to do is match that together to say, “Yes, these are both hospitals.”
So that’s part of the data matching part of it, and then we have to make sure that the data that’s along, that matches that particular parcel is accurate. Who is the owner? Is the outpar– is the components around it? What’s the zoning? Different kinds of permits. What’s there? So we actually go out and determine if this is accurate because you want to be able to make a good decision on solid data.
Then we started there Now we have AI comes into the picture. With AI, now we can actually start to replicate some of those decisions that you make in your gut. We had a gentleman come in here who’d been doing this for, forty, fifty years, and he looked at Basil and said, “Yep, if I was to do that in the back of a cocktail napkin, that’s exactly the way I would do it.”
So how do we take that knowledge, that gut instinct, and we put it into an AI model? So what we’ve done is we’ve built a financial model where the AI hits that, then looks at the data and comes back and makes a recommendation. Will this particular property, piece of property work for your particular use?
So if I’m a multifamily person, if I’m building a restaurant, or if I’m gonna build a gas station, anything like that, we can then take the AI model, look at our financial model that we’ve built, which is proprietary, and kick that… look at the data and kick that back and say, “Yes, on a scale of one to one hundred, we think that you have a sixty-five or seventy percent probability of being successful.
Now, here’s the small things you need to change, maybe permitting, housing, tr- traffic counts, something that needs to be changed. That’s all you’ll need to do to make this work for your particular use.”
Brian Thomas: Amazing. Thank you. And I know there’s a lot of data out there. You talked about that. Comes from many different sites and sources.
A lot of it’s buried in various places. And, you know, traditionally it took a ton of human capital, analysts hundreds of hours to get that output, right? With your platform, you’re able to pull in all this data, get it cleaned, and then analyze it with AI, and able to save not only a ton of time, but actually get a, more efficient process, but a, a better output. So, I really appreciate that. Doug, you-
Doug Sullinger: Let me give you… Let me give you an example of what happened to one of our clients. He would look at… He came to us and said, “I would look at fifty different projects in a given month, and I might, might do the due diligence on one or two.” With Baizel, he was literally able to flip, flip that around.
He now can go out and look at those fifty, and he now knows by just looking at Baizel, takes him a couple, take, takes him a minute or two to look at it in Baizel, “I can eliminate forty-five of those, and now I just look at the fifty that actually work for me.” That’s the real impact on a, on an investor in this business
Brian Thomas: Amazing. Thank you so much. Doug, you emphasize speed, execution, and practical application over theory. In high-stakes expansion decisions where companies are committing real capital, how do you balance moving faster with making sure those decisions are sound?
Doug Sullinger: The data, you’re gonna get, you’re gonna get to the data and almost everybody’s gonna get to the same data sets.
All right? It’s just how long is it gonna take that. The challenge you really run into is if a piece of property comes available, and I’d say seventy plus percent of the properties that we sell here are off market. If that property may come available… What I mean by available, maybe there’s been a change in the family, change in ownership or something.
Something’s happened that that property is now available, but it hasn’t list- it hasn’t hit a listing site like a CoStar or anything like that. Most people need to try to get to that as fast as they possibly can. What we’re allowed to do, we look at every piece of data, every piece of property out there, not just what’s on the listing sites.
So, you can constantly be searching for what you’re particularly looking for that fits your particular use on an ongoing basis in a particular geographic area. So now, when that thing be- when that piece of property becomes available, or if it just fits your particular need, you know, you or one of us, one of our brokers, can go out and reach out and talk to the owner of that and say, “Can we get that available?”
Well, the speed is if we get to it before the next guy does, that may be the only opportunity that for that particular type of a use becomes available in the next six months. Well, now you have excess capital that’s sitting out there that you may not be able to use. You may run into ten thirty-one problems or something like that.
Speed is absolutely the most important thing in real estate because there’s such a shortage of real estate in what we call the Southern Smile States. So you’ve got to get there fast, and you’ve got to be first one there, and then you got to be able to get there early enough so you can get it purchased at a good price.
And so speed is absolutely the most important thing in this because if it’s not gonna be you, there’s a whole bunch of other people be- right behind you that’s gonna want it. I can tell you about a couple of areas that are the hottest areas right now. Multifamily, I get calls for multifamily properties all the time.
If you don’t find those off market, don’t get to those things fast, you won’t be able to get them. You’re not gonna be successful. Same thing with shopping centers. We have a ton of people looking for shopping centers, but there’s only so many of them, right? So if my mo– if my thesis and my investment strategy is one of those two topics, I got to get there right away and get it off market before the next guy gets there, or I’m just not gonna be successful in, in real estate
Brian Thomas: Thank you. Really appreciate that. You talked about that, you know, everybody can get this the data and provide an output, but how fast and how accurate will it be? You talked about that, that you look at all the data, not just those properties that are being listed. Obviously you’ll have more robust data at your fingertips, and speed is really your competitive advantage, and you talked about that.
So thank you. Doug, the last question of the day, as we look ahead to the future, how do you see AI reshaping commercial real estate over the next few years, and what should operators be doing now to prepare for that shift?
Doug Sullinger: This is a great question. We were just in Vegas last week, and we saw an autonomous store.
So, if you think about autonomous stores, we’re used to kind of vending machines like that. Where I see technology going is that we’re gonna have autonomous almost everything. We’re looking at autonomous cars, we’re looking at autonomous storefronts. We’re gonna be looking at autonomous restaurants altogether.
At some point in time, we’re not gonna go in and have the, the high school person sitting there taking our money and, and you know, and flipping our burgers. That is gonna go away. You’re gonna have an entire Wendy’s fr- Wendy’s store run by, like, two people, and it probably has maybe, you know, one shift a, a, a day or something like that.
We’re gonna go to where the human touch is pers- really gonna go away. We keep hearing about how a certain percentage of jobs are gonna go away in this world and, and because of AI, and that’s true. And I c- I always say there’s three types of individuals out there. There’s people that are gonna have their jobs eliminated.
You know, the person that flips a burger probably will because you can automate the burger flipping, okay? There are gonna be the people that are gonna have AI applied to their job, and there’s still gonna be some human interaction that they still have to apply to that. AI won’t be able to read, won’t s- won’t be able to get away from that gut instinct.
And then the third category is gonna be people like ourselves. We are gonna be driving which, where AI can be applied in, in, in our world today. Processes will constantly be improved. We can do things a lot faster. But the, what we’re able to do with AI, we’re just scratching the surface. We have agentic models now where it can actually start to think for you and not really, I wouldn’t quite say think, but it actually helps you make analysis decisions.
We’re gonna go to the point where it’ll literally make the entire contract for you, and it’s gonna go through the entire process. And we’re not that far away. And it’s there– really gonna be depending on who adopts it. If you look at, like, China, for example, they’re very used to having people follow them around.
They’re used to having– following their cell phones. They’re used to having interaction. Literally, somebody here could ha– you know, if you had, had, had a cellphone, you could walk up to one of these autonomous stores. It can literally deliver you what you want to eat. It can literally report that stuff back into your, your mobile app that you have that says, “Hey, I’m only gonna eat these certain things today, and now I can stay right within my diet, and I can keep running and moving on.
I don’t have to handle any money. I don’t even… All I have to do is swipe my card.” That type of speed and that type of impact on our world is coming, and it’s gonna come very, very fast Where we’re gonna be three years from now, it’s gonna change, like, all decision-making. Look at just– look at drones today.
Look at how we fight wars today. All these things are gonna happen where there’s gonna be a point in time where there’s not even gonna be a human being fighting that war. It’s gonna be somebody that’s pushing in the buttons, and that’s all it’s gonna be. It won’t even be a joystick anymore. So where we’re going, it’s- I, I think that we’re– my opinion is autonomous act- auto- autonomous real estate for any kind of thing that takes any human beings, even, even looking at how bulldozers are run today.
I mean, I was raised on a farm. My dad’s combine is completely run by GPS, and it’s been that way for a long time. This is the kind of things we’re gonna go to, to where the human interaction on manual, manual task is gonna be completely gone, and it’s gonna be nothing but autonomous in the future, and AI is gonna run all of that.
Brian Thomas: Thank you. Appreciate that. You talked about that recently. You saw– You were– I think you were in Vegas and saw these autonomous stores and we’re seeing that today. Anything that really can be handled on the software side website can a-absolutely be managed by agentic AI. But you talked about the future, not just on autonomous stores, but autonomous cars, restaurants, purchasing, banking.
The whole nine yards will obviously be automated or will have agents running that stuff. And the human touch will be going away, but I think human touch will certainly be at a premium and I think people will still want to have that at some point. But I appreciate your insights, really do. And Doug, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Doug Sullinger: Great. Thank you.
Brian Thomas: Bye for now.
Doug Sullinger Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
