11 May 2026 · 22m · Elad Gil, Alexander Taubman · 24 quoted facts
Alexander Taubman argues that AI's biggest payoff in the real economy comes from owning service businesses and transforming them, not from selling software to them. Long Lake buys companies, deploys its shared AI platform, Nexus, and uses the extra productivity to grow rather than cut staff. Its agreed $6.3 billion deal for Amex GBT is presented as the biggest test of that model.
The central tension is between the usual private-equity playbook of buying, cutting costs and flipping, and Long Lake's long-term, Berkshire- and Danaher-style approach. Taubman says real AI transformation takes years of change management and engineers embedded on site. He claims this compounds into better talent, happier customers, faster growth and a lower cost of capital, which lets Long Lake outbid rivals.
Taubman says that when you only sell software you don't share in business outcomes. Owning the company lets Long Lake change processes directly, and engineers sit with employees in the field, who are treated as the customers.
About 80% of Nexus infrastructure is reused across industries, so deployment now takes days instead of the year it took on early deals. The remaining work is mapping workflows and cleaning data for each business.
In labor-heavy services, growing 20% usually means hiring about 20% more people, which eats most incremental revenue. If AI makes teams 30-40% more efficient, margins on new revenue rise and growth becomes attractive, as with software.
Taubman says staff with better tools are more productive, can be paid more, and don't want to return to manual busywork at competitors. That helps retention and recruiting and drives growth.
Taubman says the transformation takes multiple years, so selling after building the best company would make no sense. He cites Danaher and TransDigm as models that compounded by consolidating industries over decades.
It means using AI-driven transformation as the reason to buy a public company and take it off the stock market. Host Elad Gil says he believes Long Lake's agreed $6.3 billion purchase of American Express Global Business Travel is the world's first, though he flags he could be wrong.
Nexus is Long Lake's shared AI platform that sits between AI models and a business's data, workflows and skills. Taubman says it automates routine work so employees can serve more customers, and that it works with any AI model.
Taubman says no: the focus is growth and customer experience, and more productive people mean you want more of them. He says team members are paid more and retention is very high, though these are his own claims.
Taubman says Long Lake offers permanent, long-term ownership plus an embedded AI engineering team and a ready-made platform. Founders can also roll over equity and share in the upside.
Gil describes the usual playbook as buying with debt, cutting costs and flipping within a couple of years. Taubman says Long Lake intends to hold forever, modeling itself on Danaher, and to grow the businesses.
Stated by the speakers. Each quote matches the transcript, which shows what was said, not that it is true.
Long Lake Management agreed to acquire American Express Global Business Travel in a deal valued at $6.3 billion.
“you've agreed to acquire American Express Global Business Travel, the world's largest corporate travel platform, for 6.3 billion, which is pretty amazing.”
Long Lake Management had completed roughly 30 acquisitions before the Amex GBT deal, based on transforming businesses with AI.
“And before that, you've already done 30 acquisitions under this premise that you can buy businesses and transform them with AI.”
Alexander Taubman says roughly 80 percent of the infrastructure of Long Lake's Nexus platform is shared across its industry verticals.
“Um, I'd say roughly 80 of the infrastructure is shared across the verticals, and then there's a lot of work to take it and deploy it into those end markets.”
Taubman says it took Long Lake over a year on its first acquisitions to realize AI's potential in business outcomes.
“you know, in the beginning, it took us over a year with our first acquisitions to actually, you know, find the the real potential of AI”
Taubman says Long Lake can now deploy Nexus within days of partnering with a company.
“But now, within days of partnering with a company, we can deploy this very quickly and see immediate impact.”
Taubman says Long Lake's homeowners association (HOA) business is the fastest-growing company in the HOA industry and is growing organically.
“We're fastest growing company in the HOA industry. Now we are growing organically.”
Taubman says the acquired HOA businesses grew about 0-5% a year in volume before acquisition and now grow more than 20% a year.
“they were typically growing zero to 5 a year in terms of volume. We're now growing 20 plus a year.”
Long Lake's co-founder and chief technology officer, Rasmus, met Alexander Taubman through an early investor and board member.
“Rasmus, our our co-founder and CTO, uh, he and I were connected through one of our f, you know, early investors and board members.”
Taubman says Long Lake's early team included people from Palantir, Ramp, Robinhood and Glean.
“And people from, you know, places like Palantir, Ramp, Robinhood, you know, um, some of the top glean, some of the top, um, sort of modern AI and data, uh, companies.”
Taubman says a Long Lake co-founder who leads mergers and acquisitions came from the private equity firm GTCR, where he worked on its most profitable deal ever the month before leaving.
“one of our co-founders and M. A lead came from GTCR. He actually worked on the most profitable deal in their history, the month before he left to come to Long Lake.”
Taubman says the travel business now called American Express Global Business Travel was started in 1915 by American Express to help its traveler's check customers leave Europe during World War I.
“this is a this is a 111 year old company. It was started in 1915 by American Express as a way for them to get their travel checks customers out of Europe during World War I.”
Taubman says Amex GBT acquired Carlson Wagonlit Travel late in the previous year, and that Carlson Wagonlit was founded around 1876.
“Carlson Wagon Lead, which they acquired late last year, was founded, I think, in 1876.”
Taubman says Long Lake keeps a list of 15 to 20 target industries, and travel was always on it.
“We have a whiteboard of call it 15, 20 industries that we think are very high value for us to focus on. And travel was always one of them.”
Taubman says travel appealed to Long Lake because it is mission critical, has a high cost of failure, and most trips generate revenue.
“it's a mission critical service, it's high cost of failure, um, most trips are revenue generating.”
Taubman says Long Lake's stated plan for Amex GBT is to build on the company's existing AI transformation strategy.
“our vision is to really double down on the company's existing AI transformation strategy.”
Taubman says Danaher Corporation, which began in manufacturing and moved into life sciences, is a model that inspired Long Lake's strategy of compounding through an operating model.
“So part of what inspired us always about, you know, the Danahers of the world is they were able to compound.”
Taubman says his family business, started by his grandfather and run by his father and an uncle, was a 75-year-old company that the family recently exited.
“my grandfather started, my dad, Ru- an uncle ran for for for 75 year old company that we recently exited.”
Taubman estimates that real enterprise AI use cases are only around 1 percent penetrated in the economy.
“AI is very, very underpenetrated, it's probably around 1 penetrated in terms of real enterprise AI use cases.”
Taubman says Long Lake's pitch to acquired companies includes engineers who effectively work in their offices for about two years.
“our extraordinary engineering team will s basically live in your office for the next two years, helping you fix all your problems.”
Taubman says that in Long Lake's first four verticals, original founders and leaders have rolled over significant equity into the new business.
“in our first four verticals, service lines that we've gone into, we have significant rollover participation from the original founders”
Taubman says Danaher and TransDigm showed that a strong acquisition currency lets a company avoid losing deals on price because it can operate acquisitions better.
“Is that, you know, if you can establish a currency, you can actually, you know, not have to lose deals over price, cause you can operate the deals better.”
Taubman says labor-intensive service companies keep only about 20 cents of each additional revenue dollar because most goes to added labor.
“you only keep $0.20 on the dollar of every incremental, uh, dollar of revenue that comes in, because, you know, most of it goes to incremental labor.”
Taubman says AI can make existing teams 30 to 40 percent more efficient so they can handle more customers.
“when you make your existing teams 30, 40 more efficient and they can handle more customers.”
Elad Gil describes the traditional private equity playbook as buying a business for a couple of years, loading it with debt and often cutting costs before flipping it.
“The traditional private equity playbook tends to be very short-term, right? They'll buy a business for a couple years, they'll put, they'll load it up with debt.”
Introduces Long Lake's agreement to buy Amex GBT for $6.3 billion and its roughly 30 prior acquisitions, framed as AI-driven roll-ups.
“the world's first ever AI take private, where you've agreed to acquire”
Explains the shared horizontal AI platform and why deployment time fell from over a year to days.
“within days of partnering with a company, we can deploy this very quickly and see immediate impact.”
Describes organic growth rising from 0-5% to 20%+ and how better tools help retain and attract staff.
Argues ownership aligns incentives and enables the change management that AI adoption needs.
“by actually owning the companies and and owning those customer relationships directly, we can drive better, better results.”
Covers how Long Lake combined AI engineers and private equity dealmakers through personal networks.
“it's actually really hard to sell software into these services.”
Taubman explains the company's history and why travel was on Long Lake's target list.
“It was started in 1915 by American Express as a way for them to get their travel checks customers”
Contrasts Long Lake's permanent-capital approach with flipping companies, citing Danaher's compounding model.
“I'd wanna own that company forever and compound on that advantage for decades to come”
Explains why sellers choose Long Lake and why AI turns labor-heavy services into high-incremental-margin growers.
“you only keep $0.20 on the dollar of every incremental, uh, dollar of revenue that comes in”
So, to No Priors, we're joined by Alexander Taubman, the co-founder and CEO of Long Lake Management. Long Lake recently announced their intent to acquire American Express Global Business Travel for 6.3 billion in what I believe is the world's first AI take private. They have previously bought around 30 companies, and they transform and optimize them with AI. So we're very excited to have him on board today. Alex, thanks so much for joining us today on Priors.
Pleasure to be here. Thank you for having me, Lon.
Um, you just announced what I believe, and I could be wrong on this, but I think it may be, um, the world's first ever AI take private, where you've agreed to acquire American Express Global Business Travel, the world's largest corporate travel platform, for 6.3 billion, which is pretty amazing. And before that, you've already done 30 acquisitions under this premise that you can buy businesses and transform them with AI. What some people are referring to as AI-driven rollups or AI-driven, um, uh, buyouts.
And so I, it's very exciting to have you here and learn more about your business. You mentioned you have this Nexus platform, which helps your employees serve their customers better and automates a lot of the work. Could you give examples of some of the things that that automates, or how it helps them in the context of HOA? And I know you're now in four other verticals or three other verticals, and so what you do kind of crosses across the different businesses you're involved with.
yeah, that's right. So we've taken an approach since the beginning of investing very heavily in our horizontal AI platform, which we call Nexus. Um, I'd say roughly 80 of the infrastructure is shared across the verticals, and then there's a lot of work to take it and deploy it into those end markets. And the deployment R involves mapping workflows, understanding data sources, cleaning up data sources, integrating with them to make them easier for the models to access.
And sort of, our Nexus platform sits in between the models on one side, and we're model-agnostic, and the data sources, the skills, the workflows of the business. And so that takes a lot of customization and significant applied AI engineering capabilities, which we've built at Long Lake. So once we can take that platform, we buy a company now, or partner with a company now, very quickly, you know, in the beginning, it took us over a year with our first acquisitions to actually, you know, find the the real potential of AI, uh, and see it in the in the business outcomes.
But now, within days of partnering with a company, we can deploy this very quickly and see immediate impact.
So you can buy a company, and then within a couple weeks, you have instant margin lift because the employees of that new acquisition just go on a platform you've already built for similar businesses. Yeah, what Is that correct?
we what we see is instant time savings. And then the question is, how do we grow to give our team members? So we actually invest very heavily in growth. We're actually not really, you know, we're not focused on cost saving, we're actually focused on driving growth and customer experience. That's our, that's our big, and what we've seen, it's a much more powerful model because it's our view of AI is it's incredibly positive. Some, I know this is a little bit of a narrative violation, but we actually think AI makes people more productive, and we have more productive people, you want more of them.
When your customers are happier, you grow faster, you actually create jobs and everybody wins. And so we're seeing this in our companies. We're fastest growing company in the HOA industry. Now we are growing organically. We when we invested in the businesses, they were typically growing zero to 5 a year in terms of volume. We're now growing 20 plus a year. And that's because we've made our team members, we've given them extra capacity to go and serve more customers.
We actually have better, uh, more attractive customer acquisition economics, um, cause we can serve those customers at incrementally lower cost with better products and services. So we've been able to take sort of the the software style playbook of go to market and apply it into these sleepy industries. And and I think it's a win-win-win.
hm, hm. It must be hard for your employees to go and work anywhere else in the industry then, because if they're dramatically more productive, they're doing less busy work. Have you found that you've decreased employee churn, or been other That that's things you've seen?
right. We've seen very, very high retention of our team members across all of our acquisitions. Um, and actually, this is the vision, this is the vision. Long like we, we wanna basically be the best place to work in every industry that we operate. So we can get give the best people the best tools with the best customers, and that flywheel becomes self-perpetuating. Because if you now leave Long Lake, or you leave our one of our partner companies to go to a competitor, you have to start doing all this mundane work again.
That you 25 of your day, 30 of your day, you have to go do that again. And the the the thought of it's like, it's like giving up email or something, you know, you're not gonna, it's just so. Actually, we've been started to become a real talent magnet in these industries, in our companies. And by the way, we can pay people the most because they're the most productive, they're actually making more money, and we're we're delighted about that.
So we can pay you the most, give you the best tools, and we're growing the fastest. Um, you know, that's part of our vision is it's just it's, it's really making things better for team members and customers. And by the way, the other important thing is you give your team members superpowers with AI, the customers are much, much happier. So we're seeing customer retention going up, we're seeing response times much faster, errors going down in sort of things like board reporting, budgeting, email, you know, and, uh, that's driving up customer retention.
hm, hm. Oh, that's so cool. Why? Why do this via acquisition versus just offering software to people? In other words, the traditional Silicon Valley playbook would be, you know, you find the HOA industry, you realize that there's a need in terms of software. You build software for the industry, and then you sell it as a vendor, and in this case, sell it as a sort of AI product or tool. Um, why not do that? Or why did you decide to go down the acquisition path?
we. We think that you can drive better win-win business outcomes with deeper alignment, and so by actually owning the companies and and owning those customer relationships directly, we can drive better, better results. Software companies are wonderful, we partner with many of them, but when you're just selling software and you don't actually then care what happens with the with the business outcomes, you just don't see the same business And your engineers outcomes.
are just viewing your employees as their customers in some sense, then, is that correct?
That's right, our our team views our employees and our team members in the field as the customer, and that feedback loop internally, that's the other point is we have a much tighter feedback loop. So, you know, the the old skunk works thing of you want the engineers in the factory to be co-located so you can have more innovation, that's what we have at Long Lake. So our team members and our engineers are together in the field all the time.
I think there's of our engineering team, they're probably in 20 different states right now, sitting with team members across our architecture business, across our HOA business, across our HR services, or, you know, specialty tax business. And so they're sort of, um, and and there's a deep amount of change management that's involved. So this is a lot of, you know, sitting with the team members, understanding their pain points. And so there's a real like solutions orientation of how do we take the pain point we and then we build a a tool within Nexus to solve it, and that feedback loop is really important.
So you get to better outcomes this way.
No, it's pretty amazing because I think one of the biggest issues for actually adoption of AI is, uh, change management, uh, changing processes, changing organizational design. And I guess if you own the actual company, then you can make those changes. If you're just selling software, you can't really impact it very much. I think in general, um, in order to do this very well, and I've talked to dozens of people trying to do different forms of AI rollups and, uh, things like that, um, is you really need three competencies.
It seems like it seems like you need some folks who are great at the the private equity style motion of purchasing things. You need somebody who's great at engineering and building out the, uh, AI, uh, stack, and then you need really good change management. How do, how are you able to pull those three disciplines together? Because it's very rare. And again, I've seen very, very few, very few companies in this area who've done this. Was it a magic initial founding team?
Was it just how you've hired? I'm just sort of curious how you've, because you've also gotten exceptional engineers, which most, you know, uh, folks aren't able to get in this industry.
yeah, well, thank you for saying that. Yeah, so because we were purpose-built from day one to kind of be this, uh, cross-functional company with technology and DNA change management and M. We were able to attract, you know, the right type of people from network, and so I think 100 of our first 20 people were through network, knew them really well. And people from, you know, places like Palantir, Ramp, Robinhood, you know, um, some of the top glean, some of the top, um, sort of modern AI and data, uh, companies.
And so, you know, Rasmus, our our co-founder and CTO, uh, he and I were connected through one of our f, you know, early investors and board members. Who've we've all known each other for kind of 15 plus years. Um, we all started our careers together. And
And it's really rare, by the way, I think, for many business people to have those deep technical networks. Like, what I've observed is that often these are separate worlds, yeah, and technologists are very bad at hiring business people early on, at least in their careers, and vice versa, business people tend to be awful at hiring engineers. And so you end up with these mismatches on the early teams. So it's pretty amazing you were able to pull people out of some of these great companies.
yeah, well, thank you. I mean, I think it's a re well, it's a really exciting project. I think that's, you know, the idea of bringing AI into the real world, there's a lot. I mean, the what the labs are doing is extraordinary, obviously, and they're enabling all of this and all the, you know, hundreds of billions of investment that's going in. The models are getting part of our thesis was the models are gonna get better every day.
There's gonna be a tremendous amount in the trillions of investment, but who's gonna take all that and actually make it work in the real economy? There felt like a huge, huge gap. And so a lot of the folks that came together for our founding team actually were founders before in technology. Many of them had their own startups on the engineering team. They they they were either the co-founder, the CEO or CTO of an applied AI company.
But what people realized is it's actually, for the reasons we talked about earlier, it's actually really hard to sell software into these services. It's much better to. It's like, if you can't beat them, join them. And so what we, we're building sort of a team of founders, um, and we want Long Lake to be a place where entrepreneurial, applied AI engineers can come and do some of their best work.
And then you also have pulled, I think, some people out of great private equity firms. Um, what are some of the places that those folks have come from?
yeah, our private equity team comes from, you know, uh, our M. A team comes from top private equity firms like so Manny, one, sorry, one of our co-founders and M. A lead came from GTCR. He actually worked on the most profitable deal in their history, the month before he left to come to Long Lake. Um, he might get embarrassed for me saying this, but I think he was named employee of the month at GTCR, the month he he resigned.
Um, but, you know, GTCR, one of the top performing large cap buyout funds. We have folks from Blackstone, TPG, HIG, and mostly the reason they come to Long Lake is because, you know, even though these firms are extraordinary firms at what they do, they're not, uh, AI native. And so I think for those subsegment of those M A professionals that really believe in our thesis, there's there's not many places that look like Long Lake today. And so we can provide a unique environment for them to deploy AI into all these companies.
And and I think this led to this really unique opportunity, which is, uh, taking private a 110 year old business, which is, um, American Express Global Business Travel. And again, I mean, I, I haven't seen anything of this magnitude happen in the AI world up until now, which is pretty impressive. And I think it's a six, 3 billion potential, um, uh, take private. How did you all come up with the idea to do this? And I know you there's only limited things you can say since this is a public company and it's going through this transition, but you know, whatever you can share in terms of the thinking behind it.
well, we've admired this company for, you know, as long as I, you know, I think I've been a customer. Many of us, you know, involved in our some of our investors, you know, that have traveled a lot in their careers, have used this company as a customer. And, and by Um,
the way, this company, I think, got started when the only thing you could book on it was like, railways and boats. And, you know, again, it's been around for a while. I think this predates air travel, that's right, right, as a company. that's right. Yeah, Yeah,
this is a this is a 111 year old company. It was started in 1915 by American Express as a way for them to get their travel checks customers out of Europe during World War I. Um, and actually, some parts, uh, Carlson Wagon Lead, which they acquired late last year, was founded, I think, in 1876. Wagon Lead stands for, uh, sleeping cars in the train. It's French. So, I mean, these are these, these are businesses that have navigated a century plus worth of technology transformation, and so, and we think they're gonna be.
It's gonna be an extraordinary franchise for for another century to come. Um, but the the way we came up with the thesis is we'd actually been, you know, we have a prepared mind approach at Long Lake, we there's. We have a whiteboard of call it 15, 20 industries that we think are very high value for us to focus on. And travel was always one of them. And the reasons are, you know, it's a mission critical service, it's high cost of failure, um, most trips are revenue generating.
And you know, if you miss, you know, like a podcast with your favorite, you know, podcaster, for example,
Yeah, I've been a tr- tragic, be tragic. uh, so, Yeah,
you know, this is a, uh, te- The customer trust that this franchise has built over a hundred years is really extraordinary. And I think, and the company, actually, and and publicly reported, has done a really great job charting its future with AI transformation. And we just think we can double down on that and drive a lot of customer excellence.
uh, is there anything? I know again, you can't say much because of, you know, it's a transaction in progress for, like, a a public company, uh, but is there anything you can tell us about how you're thinking about where you wanna take this?
Yeah, and and I've said this, you know, publicly. In the press release is that our vision is to really double down on the company's existing AI transformation strategy. Um, and we see it as, you know, any industry that we operate in, we see our Nexus platform as giving our team members superpowers, deliver better customer outcomes, faster response times, faster, you know, um, disruption, uh, resolution, and imagine, basically, your travel counselor with AI superpowers. That's kind of the future we envision for Amex GBT's customers.
So I know that there's a few different versions of people who will buy companies to operate them or improve them. The traditional private equity playbook tends to be very short-term, right? They'll buy a business for a couple years, they'll put, they'll load it up with debt. In many cases, they may cut costs aggressively or teams aggressively and then flip the business. And I think you've taken an approach which I would view more as in the Berkshire Hathaway mold, which is you wanna buy businesses you can own and hold for a very long time, uh, and you kind of wanna invest in these businesses over time.
Uh, where do you wanna be in ten years or 20 years, or how do you think about, you know, where this, this all goes?
Well, look, I think it's a really big market opportunity. This is 20 plus 1 trillion TAM, like I said before. And, uh, I think we'd like to be the market leader in every segment that we're operating in, and I think there's a lot of segments to potentially, you know, add value to. So part of what inspired us always about, you know, the Danahers of the world is they were able to compound. They developed a differentiated operating model in their case, started in manufacturing and then life sciences.
But they were always able to drive better growth, better customer satisfaction, better employee retention, and ultimately better productivity. And that allowed them to, um, you know, continually consolidate all these industries over a long period of time with a lot of, uh, outperformance. And so our vision is to sort of follow in the footsteps of some of those great companies within the SER- and do it within the services sector and with our sort of AI platform as our advantage.
Um, and and I do think that there's something about the long-term nature of what we're doing. You know, it's really hard, what we're doing is actually really hard and doing it. You can't do this in a year, you can't do this even in two years, three years. This is a multi-year transformation. These are, uh, these, these are sort of compounding effects, where, as you as we talked about earlier, as you sort of give your people better tools, you get better people.
And then you can pay them more, and then they can deliver better customer outcomes, and then you can grow faster. That's not a one month, two month cycle, that's a two, three, four, five year transformation cycle. And then what are you gonna do? You're gonna do all that, you're gonna build the best company in the industry, and then you're gonna sell it. That just doesn't make sense to me. I I'd wanna own that company forever and compound on that advantage for decades to come, uh, and then extrapolated into ancillary areas and other service lines.
And so our vision really is to be a long-term owner, partner to world-class services companies. And and by the way, if I was a a founder-owned business who had built a great business over 50 years, you know, I'd love to know that. The next steward of that company is gonna be a long-term investor and a long-term steward of of the employees and the customers. And so that's part of our vision as well. We we've designed Long Lake, part of it is, you know, I grew up in a family of entrepreneurs and we had a family business that my grandfather started, my dad, Ru- an uncle ran for for for 75 year old company that we recently exited.
Actually, um, and uh, when we designed Long Lake, I designed it with that mindset of sort of build the product you yourself would wanna use. Which is, I would love to be, you know, if I was a seller of an asset partnering with Long Lake, and that would, that's our ambition.
So one other thing that I've noticed is that often it seems like you, you win a lot of the, uh, companies that you are bidding on in a competitive process, or, in some cases, you're the only person people wanna sell to. Could you explain why that is, or what? How that's shifted over the last two, three years?
Yeah, thank you. Um, we have had a really good suc- Our message has really resonated with, uh, with business owners and management teams, I think, because I think it is solving a really important need. Which is having a long-term, permanent capital partner is already a wonderful thing, but having that partner with deep applied AI engineering expertise and a platform that you can deploy day one.
cause these folks never see anything like that, right, in terms of the industries that they're currently in.
Yeah, the we have to, you know, AI is very, very underpenetrated, it's probably around 1 penetrated in terms of real enterprise AI use cases. And when you think about sort of the, you know, the overall economy, first of all, 99 of businesses in America are are small businesses, and they don't have access to the resources of big companies. But even big companies, you know, h- are having a hard time figuring out, you know, how to drive maximum impact from AI.
So we are sort of a we're solving many needs. And, you know, in terms of the, you know, the philosophy I mentioned before of, um, we've kind of tried to design, lo- you know, the product you wanna use. As a if we were a seller, or if we were a management team, to be the optimal partner, and that's that's how we've designed Long Lake. And so we have this cross-functional team, they become your partners day one.
I mean, you get to partner with Varun or TR- you get Varun, Taras, Prateek and, you know, Jason. And our extraordinary engineering team will s basically live in your office for the next two years, helping you fix all your problems. It's a pretty good value prop. And so, and then we also encourage rollover and equity alignment from existing shareholders or management and founders. Um, and so in our first four verticals, service lines that we've gone into, we have significant rollover participation from the original founders
So that means that owners
and leaders.
of the business gets a piece of the new business in some sense, so that they benefit in the upside of the change that's coming.
That that's right, we, we're very open to that and we've been encouraging of that, cause we like to win together. I mean, this goes back to super positive sum about AI. We think we can make everyone happy here customers, team members, you know, and the business founders and management who participate alongside us in the productivity increase. And so that's why I think we've been a differentiated partner. Um, and I, my view is, as we prove this out more and more over time, and the capital markets start to understand kind of our vision and what we're doing.
I I'd like to think our cost of capital will keep coming down as well, which then further makes us a better partner to these folks. Cause we can actually pay more than anyone else. Because, you know, and this is sort of what Danaher proved in TransDigm and all these great operators over many years. Is that, you know, if you can establish a currency, you can actually, you know, not have to lose deals over price, cause you can operate the deals better.
And then, you know, you, you have a diversified platform that's more valuable and growing faster with, you know, better financial metrics.
This is, I guess, the other thing that that's related to this is you tend to grow the businesses you buy. So you're not really focused as much on how do we cut costs as much as possible, you're often focused on how do we grow top line, how do we grow revenue, how do we make our employees more productive in terms of sales and serving customers. Can you talk a little bit about that and how you approach that?
yeah, we're we are. For us, growth is, and customer, um, experience and growth and expansion is the top priority. So
And by the way, this is very true for tech companies, but it's not very true for many other types of companies. I think
well, it's interesting, I'll tell you. So this is kind of a non-obvious thing that I've observed, which is actually most of these service companies are growth-oriented, and most of these founders built these companies from their Fair, bootstraps over
yeah, good point.
twenty, thirty, forty years by knocking on doors and, you know, figuring out how to, you know, convince people to use their service in a certain market. But it's actually now it's really painful to grow because in these industries that are very labor intensive, if you grow 20, you might need to go hire another 20 people. And then you got first, you gotta find them, you gotta train them, then you have to manage them. And if you're already making a lot of money and you're kind of, you know, you don't, you know, it's, it's this.
And then, by the way, so you do all that work to hire those people. And then you only keep $0.20 on the dollar of every incremental, uh, dollar of revenue that comes in, because, you know, most of it goes to incremental labor. So that's like a very high marginal tax rate, essentially on the growth activity. So what we've done with AI is when you make your existing teams 30, 40 more efficient and they can handle more customers.
Um, it changes the whole mindset of the organization. Now you're growing, you look like a software company now, where you're now growing with high incremental margins, and that allows you to invest more in growth, be more growth oriented. And, um, that actually is one of the most, one of the most interesting and exciting things about sort of this whole AI flowing through the ecosystem is we're seeing our partners. And, you know, you could call any of our CEOs, and some of them have been running their businesses for for decades.
I think they'd tell you they're having the best time of their career now with us. Because we're actually growing, you know, like a software company, and we're seeing our team members are getting paid more and are happier, and our customers are happier. So it's been a lot of fun.
Thanks so much for joining us on our priors.
My pleasure to be here. It was a lot of fun. Thanks for having Great me.
1st interview.
Thank you, thank you, thank you.
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