Data Handling and Governance Model.

This framework formalizes how data enters, moves through, and exits SCA-controlled workflows. It defines oversight points, audit obligations, and role responsibilities for institutional AI operations.

• Input governance and source verification
• Control pipeline checkpoints and exception handling
• Human validation requirements before decision execution
• Audit-ready traceability and review accountability