Episode 150: Doyl Burkett of Integrity Growth Partners
on Building an AI Sourcing Engine

Episode Transcript   

 

 

00:03:10.390 — 00:03:12.390 · Shiv Narayanan

All right, Doyl, welcome to the show. How's it going?

00:03:12.670 — 00:03:14.350 · Doyl Burkett

It's going great. Thanks for having me.

00:03:14.390 — 00:03:19.190 · Shiv Narayanan

Yeah, I'm excited to have you on. So why don't we start with your background and Integrity Growth. And let's go from there.

00:03:19.510 — 00:05:26.870 · Doyl Burkett

Yeah. Um. My background. You know, I won't go through everything, but. Born and raised in Seattle, Washington. Went to school back east. And I've been, you know, in private equity since I graduated in late 90s. Um, last, I guess, 26 years here out in LA, I did about ten years at a buyout firm called Aurora Capital Partners and cut my operational teeth.

There was interim CEO, CFO a few times and turnaround situations. And then I took over Kayne Anderson's growth equity practice here in LA. Kayne's a much bigger firm. We were a rounding error. We were less than a billion of their 30 billion but raised four funds there. And then was trying to do something different and use technology and software to actually change how growth equity is sourced.

And so had the idea in 2017, launched in 2018, Integrity Growth Partners, um, did not go as smoothly as we had envisioned, but we, uh, we did a several deal by deals, raised our first fund over the 23 to 25 timeframe. So it was two years. It was a not an overnight success, but we did go past our our target. So we felt very good about that.

And we're mostly invested in that first fund. And we'll be going out to market early next year for our second fund. And we focus and get in later, but founder-operated bootstrap software and tech enabled business services that are called, you know, 5 to 20, 25 million usually in an ARR. Uh, high growth, high margin, where these founders are looking for help to take the next step.

And that's where we come in. We're pretty good at a very specific pattern recognition of taking things from, you know, one stage maybe like not ready for prime time, but they've got a lot of great things about them to the next stage. It's a little bit like my, my uncle used to say before I had kids. He's like, Doyl, I'm speaking to you from the future.

I know what your kids are, what you're going to focus or your what you're going to struggle with between 0 and 1. And when the kids are two and three and five and six. And so we've done that. And we can we kind of have a playbook for our entrepreneurs to help them with that.

00:05:26.910 — 00:05:33.190 · Shiv Narayanan

Yeah that's great. So walk us through that. So what does the company look like when you first meet them. And then when do you exit the business?

00:05:33.670 — 00:08:18.300 · Doyl Burkett

Yeah I'll just pick a number just to make it simple. Um, so 10 million of annual recurring revenue would be a standard, uh, business for us. They have not taken any or much in the way of capital. We are not dictatorial about that. We just like The limited, uh, institutional capital and and limited really VC because it's the it's the non VC mindset.

We don't want the raise and burn mindset that I you know I raised 5 million from Shiv. I spend it I grow and then I raise another 10 million and we're burning cash the whole time. Um they are usually they've got product market fit. They have a great customer list. They are very strong in early proof of, you know, they've proven that their sales go to market, but usually it is fairly rudimentary.

Right. So you and me, Shiv, it would be the two of us as the founders. We would be doing every sale and that's get you can get to 10 million that way. It's very hard to get to 30, 40, 50. We probably don't have somebody in finance. Or if we do, it's your like childhood friend who you know is okay. Um, you know similar like we probably have a CTO, but one example of, you know, one of the companies we backed in our diligence.

All the code was in the CTOs personal GitHub account. So we had a which can be fixed very simply. But I had we had a conversation with the founder being like, hey, we're not saying he can't be involved, but he's more of a team player or individual contributor than the guy that's going to run the whole group.

And so we'll upgrade and top grade a lot of the positions. We are very clear on the outside of communicating. It's a little bit like a dating and a marriage. We want to make sure before we get married, which is closing the deal, but we're on the same page of here's the changes we together want to make. We're usually going to be non control like a 30 to 40% owner, but we are not afraid of doing control either.

We have a few of those. And to answer your final part of the question, what it looks like when we're done is, you know, you've now got all the the deck chairs filled, right? You've got great people in all the seats you have professionalized sometimes out built out an enterprise go to market as opposed to kind of the mom and pop way of doing it.

You have a locked and loaded tech team that is, you know, strong in development and bringing usually what would sometimes be a singular or two products. Now we have multi-product would help which helps with retention and all those things that we all know and we will exit together, usually with management and the founders at like 30, 40, 50 million of ARR.

And it's a great outcome for everybody, or at least a good outcome.

00:08:18.700 — 00:08:56.560 · Shiv Narayanan

Yeah, that's very interesting. I think, um, one of the things that you said that jumps out is just because they don't have the right people on the right seats, so talk about that in the vetting process. Just how are you taking that on? Because obviously, like a company at let's say, 5 million or 10 million, they may have higher margins or like higher EBITDA or rule of 40 type of businesses.

But part of it is because they haven't professionalized. And so now they have to go and build this team and that's expensive. And so how do you factor that into your underlying thesis in terms of how you see that investment growing over time?

00:08:56.760 — 00:11:47.900 · Doyl Burkett

Yeah. So our thesis on that specifically, we usually have our own J curve as it relates to profitability. So let's say like our standard $10 million ARR business. That's like doing a half to $1 million of EBITDA. You know. So breakeven ish we will expect for the first you don't hire them right away. Right.

And we try to but let's say sometime in that 18 months we will dip into lack of profitability, even though it's growing, because we're going to throw a decent amount of, of costs into the system together. Um, you know, sometimes invest building on an enterprise sales team is not cheap to hire. Some of the best, you know, sales execs and a CRO out there.

And so we do underwrite that into our our thesis. In terms of the vetting part that you asked. Um, it's a huge you know, we'll get into this, I'm sure, later, but a very differentiated part of the thesis. How we built this out is my whole goal. And our whole goal is to get to know these founders long before they need capital.

And that's how we built our early stage AI, now full AI sourcing system. And in the end, I can tell you now we have on average about a year to 18 months between the time we first connect with them to when we close a deal. And that gives us the time and the vetting. I'll pick on you. So let's say it's your best friend from high school.

As the CTO, if we're talking to you and you start to say, hey, I know he's not that great, but, you know, loyalty. And by the way, I value loyalty hugely. He's going to be in that seat forever. And if you guys aren't comfortable with that, you know, I get that. That's why we would walk away from something like that and be friends.

You know, it's nothing negative. But we would we are looking for folks that want the to take that next step. And we're not hatchet men and women at all. We are absolutely. Looking to grow and looking to to spend. We're not trying to cut corners, but if if there is a an exhibited lack of, um, flexibility. And because we usually are non control, we can't make them do things.

So if they're giving indications that, hey, it's kind of my way or the highway and this is how I want to do it, that's probably not going to be for us what we want to see. And because we say this all the time, we're good at what we're good at. Like, I've had great businesses come to us. We're not the guys to come in in a business at 60 million of ARR and take you to a billion, like we haven't done that now.

I think we could. But similarly we try to look for that through this these months, quarters, sometimes years of building the relationship. Because that to me is the most valuable aspect of the dating process, is seeing how they go through a hiring process, seeing how when somebody doesn't perform, how they react.

And so that's huge in the in the betting.

00:11:47.940 — 00:12:00.020 · Shiv Narayanan

Yeah, totally. It's like you're looking at the culture fit their openness to like learn, openness to like collaborate and build this thing with you more than just being like a capital partner for these companies.

00:12:00.180 — 00:13:18.530 · Doyl Burkett

Yeah. I mean, one of the best examples, we close the deal. It's a great company in the proptech space, but it's fairly complicated behind the scenes, the plumbing and we we actually hired a quality of earnings folks that are very good at what they do. And at the end of the day, they couldn't ascertain this $5 million of cash.

Whose it was, was it ours? Was it our customers? Was it somebody else's? And so we said to the and it was the problem because there was really no finance function. So we said to them, the team, hey, we're going to close over this. We'll escrow it. We're going to bring in somebody after to figure it out external.

But then we our view and let's see if we're on the same page is we need to hire a guy or a girl that will own this, that they don't need, you know, titles I don't really care about that much about. I think we ended up giving the person a VP of finance title and they moved in. To CFO. But we need somebody to professionalize this.

And usually when we're sharing the information, it's they see it. It's the best way to. I don't know if you have your kids or not, but everybody thinks their kids are, you know, the prettiest, the most talented. And I've got three. And my kids are, you know, decently good looking, decently talented, but there's always somebody better.

And so if we say these things to them in a good way and not trying to be harsh and they're receptive to it, that's great. If they are strongly pushing back, that is a pretty good signal as well.

00:13:18.730 — 00:13:45.550 · Shiv Narayanan

Yeah. What are some areas beyond the people side that you guys focus in on? Because at that 5 to 10 million are level. Like there's issues and go to market like marketing and sales. We see it all the time with our clients and portfolio companies that we interact with. What about on product? Like there's a lot of innovation, especially with AI right now.

There are changes that need to come. So like what what type of profile of company you're looking for. How are you vetting that? And then what are you choosing to focus on once you're in there?

00:13:46.430 — 00:16:41.210 · Doyl Burkett

Yeah. Um, so I mean, the profile similar to what I said earlier is, you know, high growth, it's usually 30 to 80%, but it can be higher than that. Um, you know, proven product market fit, a generally speaking, a reliable customer base. We like to have enterprise, um, we will do SMB for the right deal and they have go to market.

But it's it's not fully fleshed out and usually it's not enterprise go to market. Um, they are solving a key pain point in a large industry with a very clear ROI, which we always like to see, because then it's a relatively easy sell. If I come to you and say, you know, look, if you bring this on, you will now save X dollars versus just a, it's going to make your life easier, especially in the world of AI.

But in terms of, you know, our main areas of focus, how we're going to improve the businesses. The the first one is, is go to market. And that is usually working with them to say, let us help you. We've done this a bunch of times. Bring in somebody that is a professional. Call it CRO. We'll go out and hire these killers as sales folks.

You, the founders, can step back and actually run the business and don't have to be involved in every day to day sale. That doesn't mean you're not involved in some of the bigger ones, but you're not involved in day to day. So that's the that's the first area. The second you touched on a little bit with product and technology.

We have a group that we've worked with for over a decade that does very extensive third party tech due diligence. And as you can imagine, in today's day and age, there's even for the last few years, a huge AI component to that and that we walk away from that diligence with a 30 to 50 page tomb of information that basically says, this is where they're strong, this is where they're not.

The simplest way is they have dollar signs and fires. And if the more dollars, the more expensive it's going to be and the more number of fire flames, the the more urgent it is. And so that we hand to the company and use and that's effectively our playbook or our roadmap of where we're going in terms of product development, where we need to improve certain things on the technology, where we need to get better, not just in how we develop products, but all of times the number you know, we're getting feedback from here are some holes here, holes in the people side.

And usually not always, but usually that gets involved, is involved in bringing somebody in to run that organization. So we actually match the new person with this kind of Bible of information. So that's the second one which would be on, you know, product and tech. Uh, and the basic goal, you know, the analogy I give is a lot of times we're coming in.

These companies are like, uh,

00:16:42.730 — 00:18:15.200 · Doyl Burkett

they're a really nice. They got great bones. It's a good house on a great street. They're in a great end market, but they have an unfinished basement. Their kitchen is kind of crap, you know? And our whole goal is to, by the time we get out, is to have everything be, you know, one of the best houses on one of the best streets.

So now their kitchen's done, their basement finished. So, like, you know, their techs brought up to speed their, uh, their development is they've got AI answered if they didn't have it already, etc., etc. they've got the enterprise sales. The third area we focus on, uh, pretty, pretty consistently, um, is and this is one of the easiest ways for us to sell to these companies is on the M&A side.

So a lot of times they're shocked that we found them through our AI sourcing. One of our one of our CEOs said to me one time, so their website was in Mandarin. Nobody had ever called him. He'd gone to 25 million of ARR and basically accused us of dumpster diving going through his trash. He said, how did you find us?

And nobody's ever reached out. And I said, well, we didn't stalk you, but here's how we do it and we can help you find companies. And so that's one of our easiest sells to them, is we can take what you're looking for. We can rejigger our AI to find very small, niche acquisitions. Like we just bought a very niche AI business in multifamily about a year and a half ago before AI was, you know, kind of all these buzzwords.

And it took us very little time because we can do that. And so that's a that's a third area that we significantly help with the.

00:18:15.600 — 00:18:16.079 · Shiv Narayanan

The the

00:18:17.640 — 00:18:18.840 · Shiv Narayanan

key point please keep on.

00:18:18.920 — 00:20:03.920 · Doyl Burkett

Yeah. And so I would say the, you know, the the fourth one would be um, and I guess it does more fall under people, but usually it's on it's on operations. So as these businesses get more complicated, the one I mentioned previously in real estate tech. It's a payments company. There's a lot of dollars coming in.

There's a post. When people move out of apartments, they owe money. Does it get more complicated? We needed somebody with operational expertise that has been there and done that to run that. So yes, it's a people thing, but it's also process, right? It's like, hey, let's acknowledge that this business is between 0 to 10.

You guys can handle all these things because, you know, you're entrepreneurs and you're running around and you're fighting all the fires. But as we go from 10 to 30, 40, 50, it's a much more complex operational business. So let let's bring in somebody to run that, put out a team in there. And sometimes, by the way, it's not bringing in.

Sometimes we repurpose in one of our companies, we took this woman who was one of the founders, great. She was kind of a Jill of all trades. And now she runs operations. But it's basically setting up a center of excellence for operations. And then the last couple would be the standard, which is, you know, just general professionalization, optimization and strategy.

We from the very beginning. These companies have flown under the radar because they haven't raised capital. And we start having them talk to banks and buyers, because our view is that the best companies are bought, not sold. So I'd much rather have Shiv come to me and say, I love your business, I want to buy it.

Then having me create some memorandum and for the first time you're hearing about us, or maybe only the second time, we'd rather have it be, you know, organic interest coming inbound to start a sale process.

00:20:04.640 — 00:21:52.840 · Shiv Narayanan

We'll get back to the show in just a moment. But before we do. One of the most common and important value creation levers that we hear about on the show, from private equity investors and our own PE partners, is go to market. Yet when these same PE partners bring us into their portfolio companies or new target investments that they're exploring, we find that the marketing function is quite immature, underutilized and under optimized.

And so that's a huge opportunity that we see inside these companies. And if you have a portfolio company that you feel like it's scale a lot faster to drive more pipeline and revenue, or you're looking at a new investment where you feel like that could be core to your investment thesis. But we'd love to explore that with you and figure out how we can partner with you to drive more enterprise value creation.

On the marketing side, similar to the way that we've done with major PE firms like Updata, Hg, STG, and many more. At this point, we've done hundreds of engagements across hundreds of industries and verticals, and we have a ton of benchmarks and frameworks that we bring to these engagements to help you drive as much enterprise value as quickly as possible.

So if that sounds like something that you might be interested in, you can just email me directly at [email protected], or go to our website and schedule a demo, and we'd love to speak with you about it further. And now with that said, let's get back to the show. Yeah, you opened so many threads there, I want to I want to jump around.

Let's start with the product side, and I want to get to the AI sourcing as well, because you mentioned that a couple of times and I'm sure the audience wants to learn more. But before we do that, just help me understand. On the product side, as you're vetting these companies, how are you evaluating the AI threat and how they're adjusting their product roadmaps or what they're focused on?

Like, let's get get into more of the details there. Help us understand that, because that's a critical piece, especially in today's environment.

00:21:52.920 — 00:22:15.080 · Doyl Burkett

Yeah. So the group I mentioned. So we're not uh, we like we know, we know and we know what we don't know. So I am my team and I are not technologists. We're not going to like if we got in a contest between our founders and us on who's who's better on product and tech, we would lose every day. Um, so we like to bring in experts.

So the third party expert that we use for due diligence,

00:22:16.120 — 00:23:00.939 · Doyl Burkett

they run their diligence process and compare it, compare these companies to much better funded larger businesses on all aspects of it. But let's take AI, AI risk and they come back with effectively in each area a score. And they and I would say we view AI in every case. And I think if you're not looking it this way, you're a little dim.

It's a threat and opportunity. If you're great with AI, it's it's an opportunity for you right now. It's a strength. But there's still threats. And so what they'll come back with like with one of our companies, uh, to be very, very specific, it had all this data in multifamily, but we and our

00:23:01.940 — 00:24:48.710 · Doyl Burkett

kind of AI moat, if you will, was that we were the only ones in this space that could do this. Nobody else could figure it out. This part of the market, um, and these guys did. That's great. But you that's that mode is saying, okay, well, somebody else eventually could come in. Nothing is impenetrable. And so we one of the things that came out of the AI analysis for product here is, hey, you have a weakness in that.

if somebody comes out and builds what you have and integrates AI, they could surpass you and you have an opportunity and it's I can't get it all the weeds. But if you use AI in your process, we could basically take out these third parties we were using to, um, reach some of the folks that owed money. And we can, instead of splitting our revenue with them, take all of it so it falls right down to the bottom line.

So from day one, when we handed that tomb to the new CTO, he started building out AI, an AI functionality for us to use across our platform. And he made some good progress. But he came to us and said, I think I could truncate this development if you guys help me buy a business. And that's when we turned our AI sourcing and found this, you know, $1 million sub-$1 million ARR AI business.

And so that's, I think kind of a pretty good example where it will identify holes, it will identify opportunities. It will identify threats. And then it'll comp you against other companies that are more well funded. And then we work in a postmortem with that third party consultant and the people that are running this, let's say the CTO in this case, or had a product to then address those, both those concerns, but also lean further into the advantages that we have, right to strengthen those.

00:24:49.030 — 00:25:04.910 · Shiv Narayanan

Yeah. That's a that's an excellent example. So let's jump into the AI sourcing because you touched on that again in that story. What what are you guys doing there that is different from what other firms are doing. How are you finding companies. How are you leveraging it to source deals or build out your M&A strategies for these companies?

00:25:05.430 — 00:25:54.050 · Doyl Burkett

Yeah. So we first do it to find the companies, the platforms. And then the secondary knock on is using it for add ons. But what we started with well I'll just skip to what we're doing now. But we started we built the thesis of the firm in 2018 on this simple fact that for 40 years, Sourcing hadn't changed from when TA and Summit started it.

You hired a bunch of young people, put them on the phones. The one thing that changed is they started emailing. That was the the super, super duper technological leap. And our CEOs, when I ran the group at Kayne, Shiv would tell me a couple things. They would say one, Doyl, we like you. We like your team, but we don't like talking to 23 year olds.

It's a one way conversation. So I wanted to say, how could we source with a more senior team? And then the other thing they would say is,

00:25:55.330 — 00:27:17.230 · Doyl Burkett

Doyl, if we didn't do anything different than our competition, would you invest in us? And I was like, no, of course not. You need different. Well, you don't do anything different than the rest of the growth equity. You source exactly the same way. So our thesis was if we could use at the time, early AI predictive analytics software to get all this information about these companies, bring it into a database so it continues continuously updates.

We have from doing this for 20 years. I know if you give me ten pieces of information or more, I can tell you whether it's a company we should try to reach out to. And so that's basically and this isn't publicly. This isn't like a, you know, revenue and EBITDA. These are signals like number of people how many years they've been around growth rate of employees where they're growing the employees both in terms of function and location.

You know, there's a variety of things that we get into. And so we built a proprietary algorithm based on our experience. We really dialed it in. And that was version one. Then we hired our AI guru Will Nunes, who built out version two, which is fully AI. And what we do now specifically ships. Your question is we went from a few data providers to now we have like 6 or 7, and all the data comes in into our data lake and is fuzzy matched.

So we now have a proprietary to us three dimensional view of all of this data matched for a company. So let's say, you know,

00:27:18.310 — 00:29:32.420 · Doyl Burkett

you know, How To SaaS was a business, right? We now have the best data from the best providers. He's he and we have evaluated. Then we go out with uh to web scrape and our our AI to get further information in the public domain about this these companies. So now it goes from a fuzzy match to a really kind of crystal clear, three dimensional view that's proprietary to us of that company.

Then here's where the magic happened. Since we've been doing this for, you know, 8 or 9 years, we've had data on all these companies and we've fed that into the system, and it's learned from that, and it continuously learns. And so it says, hey, is this it's a I call it the simplest Harry Potter sorting. It sorts to fit or not fit, but based on historical experiences that we have.

And then if it goes to fit, we score it. And that score continuously gets updated on an AI based on things that the company fits in. So if I thought had a SaaS was a perfect company, and then I talked to you and there are four things that are like, oh, this isn't that great. We make notes of that and the system learns from itself, and then we use AI.

And a lot of people do this now, but in our outbound emails, because it used to be, we could only specifically change a few things. We could change, like your name, where you are industry. Now we can bring in things like if you got the award for I Don't know, Best Podcast 2025 and it just got announced because it's, you know, we would be able to send you an we have to audit it first, but a one off email.

And so we get continuous continuously. We get responses from the people that respond to us being like, oh my gosh, your emails are a breath of fresh air. I'm so sick of getting these generic, you know, AI ones. Now, we built a sequence of emails that we then layered AI on top of. And so I can tell you right now the what four of this is on average, it takes us ten emails over about 12 months for them to respond.

And we have on average from there about 18 months to build the relationship to close. Those have been much longer, but it is a very clear kind of you put the sausage in the sausage making machine and it goes down a process.

00:29:32.900 — 00:30:03.020 · Shiv Narayanan

Yeah, that's that's so interesting. I guess some of the larger firms like you mentioned do have analysts and interns doing these types of phone calls and outreach processes. I guess you've automated this one from an AI from on the data side, I guess every firm has a large data set. So how do you guys differentiate or in terms of the data that you're looking at compared to, let's say, Vista and Insight?

Some of these guys, they have so much data that they're sifting through so many companies that they meet. What's the competitive advantage there?

00:30:03.460 — 00:32:01.060 · Doyl Burkett

Yeah. So I think that look, I'll lead with my chin here. Like we're not going. If it was an arms race of spending the most on data, we're going to lose on on that. Um, so what we've been very good about doing is saying, okay, what is the bet for the specific things that we know that go into our scoring algorithm?

Who are the best providers for that? Um, and look, they can they can figure that out as well. But the the true to your question, the differentiator that we have that the other ones have not had because they were late to the party is we've been training this system for since 2018. Um, on all of our information, most folks are not one using or doing AI sourcing.

They're doing it based on like they get the data in and people are spending time. I mean, I can tell you we've automated about 95% of the human aspect of sourcing. Most of those other firms have maybe automated five or 10%. And so but the true differentiation for us is that one, it's not the data we're sourcing with a more senior team because of that there's and the team is spending most of their time doing the actual value ad which is talking to these companies.

That's how we're going to different. We're not going to differentiate on just being on the phone. Um, or excuse me, doing the research and just blasting out to multiple companies. We have our, our folks that are sourcing spend most of their day actually talking to companies because they don't have to spend the manual time doing all the other crap that everybody else does.

But the final, final real differentiation is what I was saying earlier, which is we since we've been doing this for eight years and we've made notes on all of this, we continually trained our algorithm, and now the AI is learning from that and learning from our continuous calls. And so that's where we're very far ahead of our competition.

00:32:01.180 — 00:32:46.480 · Shiv Narayanan

Yeah, I think one of the interesting things about that is this also at the stage where you're investing, right, because the larger firms are looking at bigger deals on the down market side, I definitely haven't heard as many firms taking this type of an approach, and I think that positions you at a significant advantage, because there are quality assets and companies at that stage that that require investment.

And I was actually talking to an investor a while back about the down market investment opportunities. And he was saying like, you know, like we don't see much competition because people don't want to look at companies that are sub 10 million in a lot of cases. But there's so many quality assets that if you can invest and find them early enough, you can grow them in the right way and then eventually exit to some of the some of the bigger investments investors in this space.

So I guess this approach. Sorry. Go ahead.

00:32:47.200 — 00:33:24.470 · Doyl Burkett

You're totally right. I should have probably mentioned that because you mentioned now that I didn't probably hear it close enough. The bigger players, the bigger players we don't compete against because they are so big. I'd say all the time exactly what you're saying, which is I love being, you know, I'm a baseball fan.

I love being the Double-A or Triple-A affiliate of the Yankees or the or the Blue Jays and sell up market to those guys like, I'm happy to sell to Vista. You know, insight. They call us all the time and we're in consistent dialog and. But you're right. We we have an advantage to them on on the bigger players for how long we've been doing that in our market.

We have an advantage because almost nobody is doing it in this lower middle market.

00:33:24.510 — 00:34:23.169 · Shiv Narayanan

Yeah. And I think you guys are definitely leading the charge on that, because I haven't heard many of the firms focus down market on that because they are still based on relationship selling. And I think there's opportunities missed. Like sometimes I'm often baffled that I meet so many quality businesses that private equity doesn't go and invest in.

And so I think this type of approach would uncover that. Um, what about like as you're vetting through this, I think this is an interesting thread to keep pulling on, is as you're vetting investments through this platform, like how are you filtering out companies that maybe do have that existential risk with AI or may not be set up going forward, but or conversely, like you feel like, hey, these could be the, the, the diamonds in the coal mine where this is a huge opportunity that maybe we are uncovering because we've programed that into the AI platform versus other firms may not even notice because they're not able to even even notice the companies or uncover the data that is associated with those businesses.

00:34:23.649 — 00:34:35.729 · Doyl Burkett

Yeah. So we had I think we had one advantage here because this is pre AI, but it was, you know, predictive analytics because we were sourcing with

00:34:37.250 — 00:37:26.470 · Doyl Burkett

1 or 2 people what other firms would need 10 to 20 people to do. We saw early like in the late, you know, 20 1920, in the early 2020s that there's going to be pressure on bodies, downward pressure on seats. So one we have we have in this most recent fund, we haven't invested in anything that's a per seat software business.

I'm not saying we wouldn't, but there's downward pressure. Right. If if a company if you're selling 100 seats to or 100 seats at IBM and they now with AI can do the same with 90. You're going to have 10% down sell, which is not great for your numbers. So first we started looking at that differentiation. Um, the next thing we've done in terms of, you know, kind of teaching the algorithm or the AI and the algorithm to how what we're focused on is we started saying a few years ago because this what are the defensible moats in the AI age?

And we've this is a continuous debate that we have. And it's never going to be static, but we basically have a handful that they need to fall under these areas for us to get comfortable with, and then we need to do the diligence on it. Right. But one is like proprietary data, right? If nobody has your data, you can't AI can't learn from your data.

Another one is, you know, the regulatory space, right? If you're in a health care in the US there's HIPAA. So that is a is a very significant, uh, moat. You know, hardware is another example. I have an Oura Ring right here. We don't invest in consumer, but AI can't get into that hardware. Um, we have a remote patient monitoring business that's got hardware and nobody's AI can get into there.

We talk about human in the loop businesses like our pest control business. You can't take a human out of that. And if you did with a robot, the human still owns it. And then there's the AI native and AI forward. And so as we focus on these businesses, those the AI learns from that, that these are more likely to be fits for us.

And then to your specific question, if we start talking to a company and there are it's pretty clear to us, hey, here are the risks, general risks and AI risks. We put that we make those notes, those marks into the system and it learns from that, right. So it would say, okay, if I see another company that looks like a duck walks like a duck.

We think it doesn't have this risk. But here is the risk. Is it likely that this one has it again. And we tend to just to be clear, we want to over include the companies we're reaching out because we would still rather have that phone call and learn from talking to them that it's an AI risk because you're really it's going to be hard to do desktop diligence to really prove that out.

Um, a lot of times it does require that one call, but we will it does help us separate some very clear ones that we would never, ever want to talk to.

00:37:26.550 — 00:37:47.670 · Shiv Narayanan

Yeah. That's that's so interesting. I think a lot of firms that are listening like this is I think the future of sourcing is leveraging data and filtering out companies and, and just finding more volume to find some of these more and more quality assets. Um, we're coming up on time here, Doyl. But before we close off, if people do want to get in touch and learn more about your integrity, what's the best way for them to do that?

00:37:47.830 — 00:38:51.740 · Doyl Burkett

Yeah. So our website, IntegrityGrowth.com, is great. Um, my email is [email protected]. My parents made it complicated by not putting an E on it for whatever reason. And yeah, we I mean, look, we we love what we do. Hopefully that comes across very passionate about this space. So whether it be companies or investors, you know, we're investing, like I said earlier, the end of our first fund, we've got about two platforms left and we'll be out to raise fund three next year.

We've got some great investors from large institutions to family offices. Um, and yeah, we're very proud. We just announced our most recent deal, Prevalent AI, in the AI space of cybersecurity, yesterday. Um, and we, uh, we would welcome any, any and all outreach, uh, LinkedIn. We've got a new hire who's really doing everything for us.

Uh, Jackie, on the on the, uh, chief of staff side. And so she's helping our presence on LinkedIn. We used to basically be me running that, which was. You got what we paid for. It was pretty crap. But, uh. So LinkedIn's another way to reach out.

00:38:51.860 — 00:39:08.120 · Shiv Narayanan

Awesome. Yeah, we'll be sure to include all of that in the links in the show notes. And with that said, Doyl, thanks for coming on and sharing your wisdom. I especially enjoyed the AI sourcing side. I think that is the future inside private equity, and I think a ton of investors listening will try to go back to their teams and figure out how they can do the same.

So I appreciate you doing this.

00:39:08.280 — 00:39:11.920 · Doyl Burkett

Wonderful. Thanks. It's great to have. Great to be on. Appreciate it.

00:39:12.320 — 00:39:56.600 · Shiv Narayanan

Thanks for listening to today's episode. Before we close off, if you haven't already, go grab a copy of my new book, AI Marketing Blueprint. It just hit number one bestseller status on Amazon across multiple categories, and it walks you through a proven framework on how to scale revenue and pipeline.

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And with that said, thanks for listening today and we'll see you guys next time.