Every target now claims to be AI-ready, and every diligence pack answers with narrative. A position ledger with M-scores gives your investment committee a number it can price.
Buyers of software and services companies apply a silent discount for AI-replication risk — silently, because nobody can defend the number. An exposure assessment replaces it: which positions the target's earnings stand on, how substitutable each is, and what that does to the multiple.
Scores are calibrated and comparable across targets, sectors, and years. A shortlist scored on the same scale is a shortlist you can rank.
The assessment runs on public materials under a clean-room protocol — no source-code access, no data-room dependency, no signal to the seller. That means it fits where diligence normally cannot reach: before the LOI, across a shortlist, on a live deal where the target does not know.
Start with the one-week exposure screen. Escalate to a full replication assessment only where the screen says the risk is real.
| Position | Score |
|---|---|
| Core product | M4 |
| Structured customer data | M1 |
| Onboarding services | M3 |