Unified AI Control Catalog¶
Assessor-oriented AI governance controls, evidence expectations, confidence-labeled crosswalks, and governance-as-code artifacts.
UACC is for AI governance, security, risk, compliance, audit, and model risk teams that need controls they can assess — not just principle-level alignment.
Working reference, not compliance
UACC does not provide legal advice, certify compliance, replace conformity assessment, or create a regulatory safe harbor.
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All 35 base controls, including the 11 v0.2 core controls.
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The assessor-oriented v0.2 control catalog.
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How UACC structures controls, evidence expectations, and crosswalk confidence.
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Schema, examples, and validation workflow for machine-readable governance.
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Confidence-labeled mappings to selected AI governance and security references.
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Additional guidance for generative AI and LLM-specific risks.
Start with the index¶
If you are evaluating UACC for adoption, start with the Control Index, then review the Methodology and Control Catalog.
Source of truth¶
The GitHub repository remains the source of truth for releases, issues, schemas, examples, validation scripts, attribution, and change history.