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Governance & Enablement
Establish ongoing audit procedures, training, and human oversight protocols. We help you build the operational muscle to keep your AI infrastructure auditable and trustworthy long after deployment.
How Governance Works
01
Audit Procedures
Establish recurring audit protocols — weekly runs, monthly reviews, quarterly deep dives — with evidence retention policies.
02
Training
Train your team on the new MCP-native workflow: when to trust outputs, when to escalate, how to read audit logs.
03
Oversight
Design governance committees with clear authority over exception handling, model updates, and policy changes.
04
Continuous Improvement
Measure auditability score over time. Track drift, flag regressions, and iterate on guardrail thresholds.
Deliverables
Operational audit playbook with runbooks
Team training curriculum for MCP workflows
Governance charter with RACI matrix
Quarterly auditability scorecard
Exception handling and escalation procedures