About AIGR™
Artificial Intelligence Governance Ratings.
AIGR™ develops AI Governance Ratings for organizations deploying AI in regulated and high-accountability environments. The Artificial Intelligence Governance Ratings methodology is built around defined scope, governed evidence, critical-gate logic and controlled review.
AI governance has more frameworks than decision signals.
Organizations can hold policies, assessments, model cards and control libraries while buyers, boards and regulators still lack a concise way to understand whether governance is operating in practice.
Translate governance requirements into assessable controls.
Require traceable artifacts with owners and dates.
Preserve reviewer judgment, conflicts and exceptions.
Produce a governed outcome for executive interpretation.
Evidence before assertion
Governance maturity must be demonstrated, not self-declared.
Scope before comparison
A result is tied to the system, entity, jurisdiction and date assessed.
No masking
Critical failures remain visible even when the overall score is strong.
Change is governed
Material changes and expiring evidence can trigger re-review.
Governance should be legible to the people accountable for deployment.
The product, methodology and published materials are designed around that operating requirement.