Measure what matters
Automated evaluations that go beyond vibes. Score outputs with LLM-as-judge, run A/B tests, and ship with confidence.
Score outputs at scale
Evaluate thousands of outputs automatically with built-in scorers for relevance, helpfulness, safety, and custom criteria. Get scores, explanations, and aggregate metrics.
- Pre-built evaluators for relevance, helpfulness, and safety
- Use powerful LLMs to evaluate nuanced quality criteria
- See distributions, averages, and trends across datasets
Compare models side-by-side
Test different models with the same evaluation criteria. Find the best model for your specific task by comparing quality, cost, and latency trade-offs.
- Evaluate multiple models against the same test suite
- Understand the relationship between quality and spending
- Know when differences are meaningful, not just noise
Build your own evaluators
Define what quality means for your use case. Create evaluators with code or natural language, and run them on every output or as part of your CI/CD pipeline.
- Write evaluators in Python, TypeScript, or plain English
- Run evaluations automatically on every pull request
- Track changes to test sets alongside your prompts
Explore more features
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