Models progress through defined stages in the registry: experimental (initial registration after training), staging (under validation), production (approved for deployment), and archived (retired). Stage transitions are governed events requiring documented approval; they are not automatic or self-service.

The stage management workflow ensures that no model reaches production without passing through the full validation pipeline. Promotion from staging to production requires approval from a named role, typically the AI Governance Lead or a delegate. The approval event is logged with the approver’s identity and timestamp. This approval log is Module 10 evidence demonstrating that every production model has received governance sign-off.

When a system reaches end-of-life, the production model transitions to the archived stage. The AI System Assessor verifies the artefact’s cryptographic signature one final time before archival, and the registry records the decommission date, the end-of-life trigger, and the archive storage location. The archived model must remain retrievable for the ten-year retention period under Article 18.

Key outputs

• Stage management workflow with defined transition criteria
• Approval requirements and logging for each stage transition
• End-of-life archival procedure with final integrity verification
• Module 3 and Module 10 AISDP evidence