What $1B rollups obsess about (and it's not AI)

Hi all,

We've been doing a ton of work across platform, i.e. companies focused on buying and growing like businesses to scale faster. Some traditional (little tech enablement), some built with AI from the ground up, and some that are de-novo and on the hunt for their first deal.

In the next 2-3 Talent Market Fits, we'll share how a few founders are building or have built something special, what makes them special, and how they think about things like "doing their first deal", value creation levers, where AI sits, financing structures, capital allocation strategies, and more.

In a world where more businesses will change hands in the next 10-20 years than the previous 100 years, we'll see entrepreneurs "skating to where the puck is going" and looking at buying more versus building from scratch.

Our first TMF on this topic features Elliott Hyman, CEO of Lyra Technology Group, who has bought over 100 companies in the MSP space and has a nearly perfect NPS from every deal he's brought onto the platform.

More to come, and as always, shout if I can help you at all.

105 companies.
100+ deals in 8 years.
Seller NPS near-perfect.
$1B revenue.

Few days ago, I caught up with Elliott Hyman, CEO of Lyra Technology Group,  and talked about what keeps Lyra as one of the most dominant MSP rollups in the country. We didn't talk about "hype". We talked about how and why Lyra actually works.

Elliott has spent nearly a decade building and integrating, structuring deals that preserve founder leadership, and creating repeatable ops that scale. He's proven what disciplined execution in rollups really looks like.

None of it had to do with making AI do all the work.

To be clear, Lyra loves AI and they've deployed it across their organization, but they're first obsessed with the fundamentals of making their acquired businesses work.

And yet, the market is swinging hard the other way and toward the idea that AI should take on more, if not all, of the challenges of building these fundamentals.

That’s the “AI-native rollup” for you. They’re hot right now. Everyone’s chasing them. Billion-dollar hype. AI will stitch together operations, integrate acquisitions, run sales…

The story goes: "Lyra did it with MSPs. Now the next generation will do it faster with AI running the whole play."

But that story leaves out some nuance... Let's unpack it.

Rollups vs. "AI-Native Rollups"

First, let's be clear.

Traditional rollup:

• Acquires multiple smaller companies in the same industry.
• AI is a nice-to-have, not a driver

AI rollups

• Acquires companies designed from Day 1 to leverage AI as a core operational engine.
• AI isn't a bolt-on, it's baked into culture, processes, and decision-making.

There are a lot of pluses in the AI-native rollup world right now. Just to name a few:

• Centralized knowledge at scale: Consultant know-how, results, and client feedback instantly amplified across the company.
• Tech-first operations: Minimal integration and transformation friction that often cripple non-native AI.
• Long-term leverage: Founders see opportunities decades into the future because the AI backbone amplifies human effort.

Should be a silver bullet to scale and success. Right?

Talking to Elliott it became clear: just being AI-native doesn't guarantee success. AI doesn't create the fundamentals to win. In fact, many of the companies that survive and thrive will look more like the loyal services businesses we've seen than the flashy AI startups we're seeing enter the space on the daily.

Why?

Because as AI-generated outputs become easily commoditized, your real edge is going to come from centralizing AI productivity in-house while building upon the irreplaceable human aspects of the business. That means client relationships, human judgment calls, and culture.

Where AI Helps...and Where It Doesn't

AI works when:

• Automating repetitive, high-volume tasks across the org already established as foundational.
• Standardizing knowledge and processes that humans can't scale alone, or fast enough.
• Feeding insights to improve decision-making.

And AI fails when:

• You treat it as the shortcut for understanding your problems or your customers.
• You try to replace the human elements that drive retention and referrals.
• You ignore the cultural and operational backbone necessary to scale.

As Elliott says: “The engine in any company has to exist before the tech can accelerate it.”

How to Do It the Right Way... AI Rollup or Not

Elliott shared, “Rollups in general live in gray areas. You have to be comfortable with that. One of the biggest pitfalls I see is investors trying to fix what's already working, or forcing a template playbook, before they take the time to understand the engine they just bought.”

That's exactly where most people get it wrong and today, AI is only amplifying the problem. Everyone wants to treat AI like the strategy itself, when in reality…

Many rollups fail when they expect tech to be the strategy. The truth: the fundamentals have to be rock solid before they can carry acceleration.

Elliott's playbook can seem counterintuitive by today's standards. But it's blunt, disciplined, and maybe what a lot of us need to hear right now whether in traditional or native AI-rollups…

• Start with humility. Founders built something valuable. Listen first, ask questions, then decide where to add value. Most "strategic" mistakes happen when acquirers replace curiosity with conviction.
• Let businesses breathe. Respect independence. Sometimes the fastest path to scale is less, not more.
• AI is a feature, not a product. Build your operational backbone first: solid revenue model, talent, processes, relationships. Then let AI amplify what's already humming.
• Integrity isn't optional. Do what you say you're going to do. Reliability compounds in a market drowning in promises.
• Seller wins drive referrals. Keep integrations light, preserve brands, respect leadership. That's not “soft.” That's a referral engine money can't buy.
• Data before AI. If he were starting Lyra today, Elliott's Day 1 priority would be building a robust data infrastructure that AI can then actually use. Foundation first, tech second.
  
  

Your First Deal

It's easy to look at Lyra and see the powerhouse it is today, but Elliott's first deal was anything but perfect. He joined a week after acquiring the MSP Wolf Consulting (his first time in IT services!) and tried just about everything to drive growth. “I mean, we tried everything,” Elliott shared.

Most didn't work.

But he learned that success didn't come down to forcing playbooks or even old (and I mean old) reliables…citing he even tried car wraps and radio jingles. Instead, success in rollups came down to three fundamentals:

1. Fragmented market
2. Solid revenue model
3. Sticky services with predictable cash flow

And every deal since has followed the same rule: get the fundamentals right, then let value levers amplify them.

The $1B Companies All Do the Same Thing

Whether rollup or AI-native rollup, every company that scales into the billions does this in some form: nail the fundamentals before they add tech as an accelerant.

As Elliott put it: “Look at Amazon. The biggest company in the world didn't start with AI. They started with a maniacal focus on operations and customer experience.”

If people care about “AI” and then the core of their offering, they're going to miss the boat. Building a platform is a people-intensive people business, and you need to have equal intensity on the people as you do your AI differentiators. (In fact, Elliott shared the biggest swing he actually took was doubling down on the people hiring in the first-ever down year and well… that story clearly has a good ending.)

My take

If you're building today, it's tempting to believe AI is the shortcut. It’s also easy to spend all your time trying to make AI the foundation of your differentiation.

But that takes what’s already hard, finding the right deal, doing the deal, and driving growth… and makes it even more complex with tech resets, behavior change, and adoption challenges.

Split focus is tough. If you give equal weight to AI transformation and doing the right deals, the rollup game becomes even harder.

Don’t forget the fundamentals.

And hire a damn good CTO and business partner to make sure you get AI and change management part right.

Otherwise you’ll be stuck with some really expensive, unused tech masking what could have been a great traditional rollup…