Skip to content
datatruth Get your Truth Score

Private equity · Sector and thesis-driven

Tested against your thesis, not a generic checklist.

When a fund is built around a sector, the question isn’t general AI readiness. It’s whether each company’s data can run the specific AI plays your thesis depends on. We pull those plays out of the thesis, map each to the data it needs and test them one by one.

Test one portfolio company Where we fit

Starts with a 30-minute call. Commits you to nothing.

Illustrative example, not a client.

Real sample

See the memo a portfolio company would receive. A full Truth Score Read on 72,837 records in 7 exports from CRM, finance and HR. It scored 59 out of 100, Band C, significant work needed: 823 finance customers with no CRM account, and only 13% of deals reconcile to invoices.

Read the sample memo

Real engine output on generated test data, not a client.

The challenge

Generic readiness measures everything and answers nothing.

A statement of what AI can do for a sector doesn’t help you underwrite a company. The value sits in a handful of use cases: demand forecasting in distribution, pricing and rebates in manufacturing, churn in software.

Each of those leans on specific records agreeing across specific systems. A read tuned to the plays that carry your case, and honest about the ones the data can’t yet support, is the read that matters.

The thesis names the plays. The data decides which ones run.

How to read the card above: a Truth Score™ is a score out of 100 for how far the data can be trusted. Beside it is a Leverability read (which AI plays the data can run now, after fixes, or not at all; nothing to do with debt). Each play sits next to the target in the plan that leans on it.

How it works

From the thesis to the records, play by play.

  1. 01The thesis

    The plays, pulled out

    We read the thesis or value creation plan and list the AI plays in it, and the growth targets that lean on them.

    AI Investment ReviewMore

  2. 02The data

    Each play, mapped

    Every play mapped to the records it needs: which systems, which fields, which matches between them.

    Truth Score ReadMore

  3. 03The companies

    Each company, tested

    Deploy now, needs work or blocked, company by company, on the same pillars, rules and caps.

    Truth Score ReadMore

Questions

Asked plainly.

What investors in this strategy ask before a portfolio company sends a single export.

Book the call
Do you have sector benchmarks?

No, and we won’t invent them. The read tests the company against your thesis and its systems against each other. Comparisons are between companies you’ve had read on the same method.

Can you work from our investment memo?

Yes. A thesis, investment memo, 100-day plan or value creation plan all work, under NDA like everything else.

Which AI plays can you test?

Any play whose data sits in systems that export: forecasting, pricing, churn, lead scoring, collections, close automation and more. Some, such as document intelligence, are assessed with your team rather than from exports alone. See the use cases.

What does it cost?

A fixed fee, agreed before we start, that never moves with the verdict. It is a small fraction of the proposal it tests; if it wouldn’t be, we’ll tell you on the call. Our first clients get a founding rate in exchange for a private reference call once they’re happy with the work, only with their consent. We never name a client, fund or target publicly without written consent.

Other strategies

The same method, pointed elsewhere.

Test the thesis against the records.

Send the thesis and one company’s exports. Each AI play tested, within 5 working days of complete exports.

Test one portfolio company See a real sample memo

Starts with a 30-minute call. Commits you to nothing.

Get your Truth Score