In audits, governance is not evaluated by intent, policies, or architecture diagrams. It
is evaluated by evidence.
For AI systems — especially those using large language models — this evidence is often
fragmented, implicit, or entirely missing. Teams know how their systems behave, but cannot
demonstrate how decisions are controlled, reviewed, or logged in a way auditors can
verify.
Graille is designed to make AI governance auditable before it is enforceable.
- Assess
Define audit expectations before enforcement exists.
- Produce
Generate explicit evidence and control gap categories.
- Enforce
Apply runtime controls only after posture is defined.