Builds eval suites with ground-truth answers, automated scoring, and regression detection so you know whether model or prompt changes actually improve outcomes before shipping.
Use cases
- Model comparison
- Prompt A/B testing
- Regression detection
Key features
- Define task-specific metrics
- Curate evaluation datasets
- Run automated scoring in CI
Related
Related
3 Indexed items
Verify before you ship
Runs the right checks—tests, builds, or manual steps—before claiming completion so “done” always means verified in the real environment.
AI cost optimization
Audits token usage, model selection, caching strategy, and prompt compression so teams scale AI features without runaway inference bills—particularly relevant for high-volume agentic workflows.
Canary rollouts
Ships a small percentage of traffic to a new build first, watches error budgets and latency, then widens or rolls back—so surprises stay small when agents touch deploy pipelines.