AI that lifts EBITDA and the exit multiple, across your portfolio.
We run the Hybrid AI Innovation Model at fund scale, building real AI capability inside portfolio companies and tracking it with AI-Maturity metrics that evidence value at exit. You get hard EBITDA gains and a credible story for the multiple.
AI moves valuation two ways.
AI improves the financials a buyer underwrites today, and it underpins the growth story that expands the multiple tomorrow.
Improve the financials
Revenue and share growth from better products and data-driven sales, lower costs through operational efficiency, and higher margins through pricing and customer experience.
Expand the addressable market
AI generates new revenue streams and reaches new segments. Data and AI insights become products in their own right, enabling new business models.
Migrate toward tech valuations
Turning a data-rich traditional company into an AI-first one strengthens KPIs and supports a credible thesis for long-term growth that lifts the multiple.
Build platform interoperability
An AI-first company connects and integrates data from customers, suppliers and partners. A strategic buyer recognizes and pays for that structural advantage.
The same hybrid method, run across the whole portfolio.
Leadership teams set ambition and governance from the top, while subject-matter experts build validated use cases from the ground up. Across a fund, the loop turns every portfolio company into evidence for the next.
And because your own people build it, the capability stays inside each portfolio company as durable value a strategic buyer will pay for, not a dependency that leaves when the consultants do.
AI value, mapped to the PE lifecycle.
From screening to post-exit, AI is a thread you can price, build and evidence at every stage.
Screening
Assess how AI will reshape the industry and score a target’s AI value potential with simple AI-Maturity metrics.
Due diligence
Define the AI end-state, size the gap that can be closed in the hold, and the related costs and risks, to set the right price.
Deal making
Secure executive commitment with a high-level AI plan, tying funding to AI-Maturity thresholds and ROI targets.
Holding & growing
Track AI ROI with operational KPIs as the company builds the capability to create value from its data.
Exit
Evidence EBITDA gains attributable to AI, plus the maturity metrics that justify an expanded multiple.
Post-exit support
Continuity in AI transformation support reduces the risk profile for a strategic buyer with an integration roadmap.
Cross-portfolio programs compound the returns.
Common ownership removes the confidentiality barriers that usually block shared AI learning.
Accelerated learning curve
Participants learn from each other and benchmark against peers, with case studies drawn from real challenges across the portfolio.
Cross-portfolio innovation
Teams from different industries collaborate, and shared solutions to common problems, from data infrastructure to AI for HR, spread across companies.
Economies of scale
Joint purchasing increases bargaining power with vendors and lets companies share critical deployment resources and cost.
A hard, recurring gain at one portfolio company.
At an industrial manufacturer, the AI work added EUR 1.02 million of recurring EBITDA, around 1.5 percent, alongside a 15 percent cut in machine downtime. Built by the company’s own people, so the gain stays after the hold.
And at fund level: across a real-estate portfolio, securely shared learning let every asset draw on the whole fund’s data, the kind of cross-company value only common ownership unlocks.
Put AI to work across your portfolio.
Get in touch with our founder. Bring your portfolio, and we will brainstorm where AI can move EBITDA and the multiple.