Intent Discovery and Classification
You do not define intents up front. After enough traffic accumulates, Insights clusters real user inputs and labels each cluster - for example,refund_request, flight_booking, or complaint_escalation - then tracks each as a first-class workflow.
| Capability | Description |
|---|---|
| Automatic bootstrap | After ~500 traces, Insights clusters your traffic and produces a labeled set of intents |
| Continuous classification | Every new trace is matched to the closest intent in real time |
| New-intent discovery | Unmatched traces are clustered daily; emerging intents surface as they appear |
| Intent status | Each intent is automatically tagged growing, declining, stable, or new based on 30-day volume trend |
| Per-intent metrics | Cost, latency, error rate, and tool usage broken down by intent |
Why Intents Matter
Without intent visibility, you have no reliable way to know what users are actually doing with your AI. Aggregate metrics stay green while a specific workflow quietly regresses. Intent tracking lets product teams see emerging use cases as they appear and lets engineering teams prioritize fixes by which workflow is causing the most impact.Learn More
Drifts
Detect behavior changes per intent before users notice them
Insights Overview
How to set up Insights and what it monitors