Portfolio adoption, not portfolio pilots
We train the people inside your portfolio companies to originate and run their own AI work. An in-house program, delivered company by company on their own systems and their own data, that leaves each business with champions who can carry it forward and a management team a buyer will pay for.
The constraint in the lower middle market
Your portfolio companies do not have data teams, platform budgets, or the runway to absorb a two-year modernization program. They have capable management teams already running flat out, and a hold period that will not wait. At that scale the only AI program that pays is one the company’s own people can run.
So that is what we build. Not a vendor dependency, not a pilot deck: champions inside each business who can identify, scope, and run AI work themselves, and an executive sponsor who knows how to lead them.
The in-house program
It starts with the champions. The PDP Assessment finds the people inside the company who are already reaching for AI on their own, who know the business deeply, and who cannot stop tinkering. They are rarely the technical experts, and that is the point: a deep expert with curiosity is worth more than a hire who would take three years to learn the business.
Then we come in and upskill them, for that company alone: a three-to-six-month engagement with three to eight champions plus the executive who sponsors them. Working sessions on the company’s own systems and its own data, each one half instruction and half working time; an assignment applied to their real work between sessions; then back to iterate. The champions learn to put solutions in place themselves. When a piece is harder than the group, we build that last stretch with them and hand it back.
- First: working environments running, data safety settled, and real systems connected with real permissions
- Then: judgment and guardrails — where these tools fail, what to verify, what never leaves the walls — and repeatable workflows instead of one-off asks
- Finally: handing workflows to people outside the champion group, and a capstone where each champion presents what they built and what it cost
- Throughout: one-on-ones on each champion’s own systems, and open office hours in the weeks between sessions
- Monthly executive coaching with the sponsor, separate from the group work
It ends with a 90-day plan drafted by the champions and owned by the sponsor, and a named list of what still needs outside help — written by the people who ran into the limit themselves, which makes it a better statement of work than any proposal process produces. The full program detail is here.
One company at a time
We do not roll this out across a portfolio. Champions have to be found inside each business, and the work has to be that business’s real work, so we go into one company, solve its problem, and leave the capability behind. When it has worked, the next company is a fresh start with its own assessment and its own people.
A baseline before, a delta after
The capability stays
Value that survives the exit
The Executive AI Cohort
The same teaching in a different room: a six-month cohort of six to eight executives, each from a different company, working on their own systems and their own week. For a sponsor it fits two cases the in-house program does not. A single portfolio-company CEO who is ready before their organization is, and operating partners who need to assess, direct, and standardize AI work across many companies rather than run it in one. The cohort in full.
The rest of what we do for sponsors
Training is the center of the work because it is what compounds. Around it, we take on the adjacent jobs a portfolio generates.
Diligence support
Do-it-with-you builds
A story a buyer can diligence
Start inside one company
A conversation about your portfolio, which company goes first, and what the assessment would show. No pitch deck.