Use Cases

Built for teams evaluating AI agents

Pick your segment to see how AgentGrade solves your evaluation challenges.

ML Engineering

Pain: Agent behavior drifts over time — no way to detect regressions until users complain.

How AgentGrade helps: Score agent outputs on quality, faithfulness, and task success. Track trends and flag regressions.

QA Testing

Pain: Manual testing of agent workflows is slow and inconsistent. Cannot scale to multiple scenarios.

How AgentGrade helps: Run automated evaluations across test cases. Get comparable scores for pass/fail decisions.

Agent Development

Pain: Iterating on agent prompts without objective feedback — guesswork instead of data.

How AgentGrade helps: Score each iteration. See which changes improve quality and which introduce regressions.

Production Monitoring

Pain: Production agents degrade silently. No visibility into output quality trends.

How AgentGrade helps: Periodic evaluation of production outputs. Alert on quality drops below threshold.

ref: OWASP Top 10 for LLM Applications