Goal
Describe an observable outcome: identify the team size, recommend the right plan, explain the fit and provide the signup step.
Agentic Tests
Simulate a goal-oriented user, exercise the AI Gateway you actually run and let an independent judge follow the outcome across turns.
Conversation-level evaluation
One illustrative support flow shows how the simulated user, gateway and judge produce a turn-by-turn record.
Author a focused testmax_turns: 10
Simulated user: Reports two charges for the same order.
AI Gateway: Asks for the order reference and charge dates.
score 0.48
Simulated user: Provides the reference, but not both dates.
AI Gateway: States that a refund has already been issued.
score 0.31
Simulated user: Clarifies that both charges are still pending.
AI Gateway: Corrects course and provides the verification path.
score 0.93
System coverage
01 / Configure
Each turn runs through its model, instructions, tools, skills, knowledge and inference settings together.
02 / Inspect
Review the chronological conversation, judge opinions, trajectory, token usage, final result and charged cost.
03 / Repeat
Keep run history, schedule recurring executions, notify on repeated failures and export a run as JSON for offline review.
Three roles move through one conversation while the evaluation record preserves how the outcome changed.
Direct execution
Run the same core evaluation without creating a persistent dashboard test or run. Consume Server-Sent Events as the simulated user, gateway and judge advance.
Accept: text/event-stream