White Paper

The Zero-Findings Standard™

Building AI governance programmes that survive regulatory examination — inventory, consequence-based classification, accountable ownership, and the evidence trail examiners actually ask for.

What It Covers

Four questions an examination turns on

01

How much AI do you actually have?

Why the governed inventory is usually the only inventory anyone built, and what a vendor-embedded and shadow sweep surfaces that a policy review never will.

02

Who is accountable for each system?

The difference between a committee and a name, and why unregistered automations fail the ownership test before they fail any technical one.

03

Is it tiered by consequence?

Autonomy times blast radius. Why classification by model sophistication produces the wrong control set, and how agentic systems tier differently.

04

Can you evidence it this week?

The artifact pack an examiner can be walked through, and why lineage and retention evidence is the gate everything else depends on.

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The ZERO™ Operating Model

Five stages, the data readiness gate, and the loop that closes.

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The Zero Findings Brief

Ongoing analysis on governance, operating models and examination.

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Engagements

Diagnostic, fractional lead, build, and annual assurance.

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Your AI governance program may look great on paper. Will it survive a regulatory examination?

Sixty minutes. No cost. You leave with a one-page Exposure Hypothesis.