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A drift is a meaningful shift in how your AI behaves now compared to a rolling baseline of its recent past. Insights computes drift across three time horizons and stores each observation for review.

Time Horizons

Drift is computed on every observation run across three windows:

Drift Categories

Computed per intent, compared to baseline:
Tracks average output length per intent. Surfaces when responses become noticeably shorter or longer than the baseline - a common signal of prompt regression or model behavior change.
Emitted alongside new-intent discovery. When a cluster of user inputs appears that does not match any known intent, Insights flags it as an input drift signal - indicating that the nature of requests hitting your AI has shifted.

Drift Severity

Each metric is scored automatically using the method appropriate for that signal type. You do not need to configure thresholds; Insights applies calibrated defaults and assigns a severity to each observation.

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Intents

Understand how Insights classifies user requests by intent

Alert Rules

Set up alerts on top of the metrics Insights tracks
Last modified on June 8, 2026