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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.

  • Control Index

    All 35 base controls, including the 11 v0.2 core controls.

  • Control Catalog

    The assessor-oriented v0.2 control catalog.

  • Methodology

    How UACC structures controls, evidence expectations, and crosswalk confidence.

  • Governance as Code

    Schema, examples, and validation workflow for machine-readable governance.

  • Crosswalk

    Confidence-labeled mappings to selected AI governance and security references.

  • GenAI Overlay

    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.