Model Drift & Regression

AI models change over time - whether through provider updates, fine-tuning, or environmental shifts. These guides help you detect and respond to quality regressions before they impact users.

In This Section

Drift Detection Identify when model behavior changes unexpectedly.

Population Stability Index Use PSI to measure distribution shifts in model outputs.

Quality Metrics Define and track the metrics that matter for your use case.

A/B Testing Compare model versions with statistical rigor.

Evaluation Frameworks Choose and implement the right eval framework.

Feedback Loops Build systems that learn from user feedback.

Regression Testing Catch quality regressions before deployment.

Root Cause Analysis Investigate why model quality degraded.