Human-in-the-Loop Quality
Treat quality as a governance design choice.
AI outputs need to meet enterprise quality standards before client delivery. Human-in-the-Loop workflows put judgment into the process without turning oversight into bureaucracy.
Set oversight by risk
Use risk tiers to determine when outputs need expert review, sampling oversight, policy checks, or automated monitoring.
Monitor quality and drift
Build monitoring, drift detection, incident logging, and root-cause review into the operational control loop.
Make decisions traceable
Define how overrides, escalations, and outcomes are recorded so teams can reconstruct why a decision was made.
Instrument the controls
A practical governance framework makes performance observable and gives teams a route from issue detection to resolution. Oversight can be calibrated to the risk of each workflow.
Signals to track
- Human override rate
- False positive and false negative balance
- Time to detect drift
- Completeness of decision trace