AI governance becomes real when organizations can connect policy, operational controls, and technical evidence. That requires more than broad principles. It requires artifact identity, registries, provenance, certification, and decision history.
CertifiedData's governance layer focuses on the technical foundations of trustworthy AI artifacts: how they are identified, recorded, verified, and connected across the lifecycle.
This hub organizes the core governance surfaces that support AI trust infrastructure, including artifact certification, registry workflows, audit trails, training data provenance, decision lineage, and supply chain visibility.
Core governance records
These pages explain how AI artifacts are identified, certified, and maintained as structured governance objects.
AI Artifact Certification
How machine-verifiable certification records strengthen trust in datasets, model artifacts, and AI outputs.
AI Artifact Registry
Why artifact registries are becoming core infrastructure for provenance, lineage, and lifecycle governance.
Auditability and lifecycle accountability
These pages cover how AI governance becomes traceable over time through audit trails and decision history.
AI Audit Trails
How AI audit trails capture the events, records, and evidence needed for later review and accountability.
AI Decision Lineage
How approvals, changes, and governance decisions can be linked to artifacts and evidence.
Data provenance and supply chain transparency
These pages connect training data, component inventory, and supply chain transparency into a broader AI governance architecture.
Training Data Provenance
Why provenance for training data is becoming foundational to AI governance and certification.
AI Supply Chain
How AI governance increasingly depends on visibility into data, models, dependencies, and lifecycle artifacts.
AI Component Inventory
How component inventories and artifact records support AI accountability and operational transparency.
Bias risk and evaluation
These pages cover how training data bias risk is documented, evaluated, and made traceable for AI governance requirements.
Training Data Bias Risk
Five categories of training data bias and how to document them for EU AI Act, NIST AI RMF, and ISO 42001.
AI Bias Audit Trail
How tamper-evident bias audit trails are built from evaluation records, certificates, and transparency logs.