AI transformation that delivers EBITDA.

Most AI projects die in pilot purgatory. I take you from strategy to implementation, with every investment tied to business outcomes.

Let's Talk
AI strategy illustration

AI is everywhere. Results are rare.

Every vendor has an AI pitch. Every consultant has a framework. But most AI initiatives fail because they start with technology instead of business problems.

The result: expensive pilots that never scale, tools that don't get adopted, and "AI strategies" that sit in slide decks.

Start with EBITDA. Work backward.

I don't start with what AI can do. I start with what your business needs: Where can we increase revenue? Cut costs? Speed up operations? Then I find the highest-impact opportunities, prove value fast, and scale what works.

1

Identify

Find the AI opportunities that will actually move your business. Not the flashiest. The ones tied to real outcomes.

2

Prove

Run a focused pilot. Fast. Minimal investment. Clear success criteria. No science projects.

3

Scale

Take what works and expand it. Build the internal capability to keep going without me.

Strategy through implementation.

I don't hand you a deck and disappear. I stay in the trenches until it's working.

This can include:

  • AI opportunity assessment and prioritization
  • Vendor and tool evaluation (build vs. buy)
  • Pilot design and execution
  • Implementation oversight
  • Team training and capability building
  • Ongoing advisory as you scale

The scope depends on what you need. Some engagements are 6 weeks. Some are 6 months.

Mid-market companies and PE portfolio companies.

I work with companies doing $5M-$55M in revenue who know AI matters but aren't sure where to start, or who have tried and stalled.

I also work with PE firms who want to drive AI transformation across their portfolios. One pilot, proved in one company, scaled to ten.

For PE Firms

I've been building AI products since before the hype.

I built and sold an enterprise ML company. Machine learning products in the early 2000s, when most people had never heard the term.

I've seen what works and what's just a demo. I know where the pitfalls are. And I've sat on both sides of the table: as the operator implementing AI and as the CEO accountable for results.

PhD in Computer Science from Princeton. I go deep on the technology so you don't have to.

Let's talk about where AI can actually help.

Tell me what you're working on. I'll be honest about whether AI is the right answer.