Comprehensive LLM assessment
From single responses to complex agent trajectories, Eval provides the evaluation types you need for rigorous model assessment.
Response Evaluation
Assess individual responses against custom criteria. Define scoring functions or use pre-built evaluators.
Trajectory Evaluation
Evaluate multi-turn conversations and agent paths. Assess reasoning chains, tool usage, decision quality.
Model Comparison
Side-by-side dashboards to compare performance. Understand quality, latency, and cost tradeoffs.
Custom Evaluators
Define your own evaluation criteria and scoring functions. Bring domain-specific knowledge to your evaluations. Support for LLM-as-judge, rule-based, and hybrid approaches.
CI/CD Integration
GitHub Actions, GitLab CI, and webhook integrations. Run evaluations on every commit, PR, or deployment. Block merges that regress quality.
Parallel Execution
Serverless infrastructure scales automatically. Run thousands of evaluations in parallel without managing compute. Fast results even for large test suites.
Result Aggregation
Automatic statistical analysis and aggregation. Confidence intervals, significance testing, and trend analysis. Know when changes actually matter.
Why Reproducibility Matters
Ad-hoc evaluation scripts produce inconsistent results. When performance changes, you can't tell if it's the model or the evaluation. Eval enforces reproducibility through versioned specs, deterministic execution, and immutable result records.
Every evaluation run is reproducible. Same inputs, same outputs, every time.