AI & Cloud Economics for Private Equity

PE Deal Advisory

This work is for two people: the PE operating partner who owns a value creation plan, and the CTO at the portfolio company who has to deliver it. Both are measured on the same thing, and neither is served by a technical report nobody in the deal room can read. Cloud economics in private equity demands the ability to translate findings into financial impact — EBITDA adjustments, valuation changes, and deal pricing decisions — which means combining cloud infrastructure depth with an understanding of hold periods and exit multiples.

Unlike general tech diligence firms that provide surface-level cloud analysis, or cost consultants who work post-acquisition, I specialize in cloud economics across the entire PE deal lifecycle. At AWS, working with hundreds of PE-backed companies provided practical benchmarks, realistic expectations, and deep insight into what cloud providers can actually deliver and how to leverage portfolio scale.

Increasingly that work is about AI. Inference is the fastest-growing line item on most portfolio companies' infrastructure bills and the least well understood, which is precisely why it is mispriced in both directions — premiums paid for capability that is a vendor passthrough, and margin models that assume scale will fix a cost that scales with usage. AI diligence and unit economics applies the same method to that problem.