The value creation plan,
in production by day 100.
We find the workflows in each portfolio company where AI moves EBITDA, ship them onto one production platform, and carry what works to the next company. Every capability has an owner, a measured baseline and the evidence a buyer will ask for at exit.
Every portfolio company is experimenting.
Very little of it reaches EBITDA.
Operating partners are asked for an AI plan at every board meeting. The pilots are real and the intent is right. What is missing is the engineering that takes a pilot into production, measures it, and carries it to the next company.
Illustrative portfolio. Real audits score every workflow on EBITDA impact, effort, data readiness and adoption risk, with the working attached.
The first hundred days,
as a build log.
One senior squad works inside one portfolio company. Each capability ships behind an evaluation suite and reports against a baseline the company’s CFO signed before we started. By day 100 the platform runs in the company’s own cloud and the run-rate has been measured against that baseline.
Illustrative five-company programme. Timings depend on each company’s systems and data.
Value you can bridge,
line by line.
Every capability reports against a baseline the portfolio company signed before the build. The value creation plan carries measured numbers, and the same evidence goes into the data room at exit.
Illustrative bridge for one portfolio company. Each line is measured against a baseline signed before the build. The multiple is the fund’s own exit assumption.
Three ways in.
Each one earns the next.
AI value creation for private equity portfolios, measured from the baseline to exit.
32 → 64