The builders don’t consult.
The consultants don’t build.
We do both.
Cohort L is an operator-led AI practice for mid-market operational businesses. We work as the AI function you cannot yet build: we diagnose the real problem, build the fix, and run it. Every engagement leaves you with a sharper asset that makes the next one cheaper.
Four principles. This is the practice, not the product.
Cortex is the platform we run on. Cohort L is the practice itself. Everything below is a property of the practice, the part a competitor cannot buy with capital.
We go in, build the fix, and run it.
We are not a consulting firm that writes decks, and we are not a vendor selling a product. We go in, diagnose the real problem, build the fix, and run it. The person in the room came from McKinsey and Advent, then built the AI, then operated it. We work as the AI function you cannot yet hire.
One practice holds all four toolkits: strategy, build, implementation, and the investor’s read.
The AI is rented.
What lasts is yours.
Models change every few months. What matters is the rule library underneath, the encoded judgment of how your business actually runs. That layer works with any model, any data source, any interface. You own the rules. If you pull our layer out tomorrow, nothing breaks.
Rented models.
Owned rules.
You buy an outcome, not a license.
An engagement is a thing that happens, with people and outcomes, not a license that gathers dust. Software is part of what gets shipped, not what gets sold. And it compounds: each engagement makes the next one sharper, because the methodology is the memory of every place we were wrong before.
Software is the receipt, not the sale.
Built for operators, by operators.
Mid-market operational companies are underserved: too operational for the horizontal AI tools, too small for the Big Four, too stretched to build it themselves. We know the seat because we have sat in it. We bring a methodology that has already been wrong in six different ways, so you do not pay to discover those the hard way.
A methodology that has already been wrong in six different ways.
The practice is the people in the room.
Christian Senye
McKinsey, then Advent. Then built a services business from two people to seven hundred, fifty million in revenue, profitable, exited in eighteen months. Then built the AI. Now runs the practice. Wharton MBA.
David Birnbaum
Twenty years an investor: Patricof, Apax, Goldman, Five Four Ventures. Board seats, PE relationships, and the pattern recognition that comes from underwriting operators for a living. Wharton MBA.
Each engagement makes the next one cheaper.
For us, and for you.
The rule library grows with every deployment. The fifth pest-control client is meaningfully easier than the first, because the rules already exist for that vertical. A competitor starting today has to run six engagements to reach our marginal cost on the seventh. By then we are on the thirteenth. The gap widens by design.
The AI itself is rented. What is hard is the rule library underneath. Every deployment sharpens it, and every client inherits the sharper version.
Four things this practice refuses to be.
We ship working software, not ninety slides.
You buy an outcome, not a login.
Rented models, owned rules.
Logged, reversible, bounded.
Cortex is how the practice ships.
Cortex is the synthesis layer we build on each engagement, the product side of the practice. If you want to see what it does, the demos live on the product site.
We work with a small number of operators at a time.
If you run a mid-market operational business and want an operator’s read on where AI actually moves the needle, start a conversation.