Braintrust

Braintrust is an AI evaluation and experimentation platform for teams shipping LLM applications who need systematic evidence that changes to models, prompts, or retrieval configurations actually improve quality before deploying them to users. The core workflow: define evaluation datasets from production logs, logged edge cases, or manually curated examples; write or configure scoring functions that assess output quality (correctness, faithfulness, relevance, custom criteria); run experiments comparing different configurations against the same dataset; and compare results in a structured dashboard that shows exactly which cases improved, which degraded, and by how much. This experiment-and-compare approach brings the rigor of software testing to AI system development, where qualitative impressions of 'it seems better' frequently lead to regressions that only appear in production. CI/CD integration runs evaluations automatically on every pull request, catching quality regressions before they merge, the same safety net that unit tests provide for functional correctness, applied to LLM output quality.

The logging layer captures production inference with linked evaluation scores, creating a feedback loop from production behavior to evaluation dataset improvement. Human annotation tools enable quality reviewers to label outputs inline without leaving the platform. Used by engineering teams at companies including Stripe, Vercel, and Anthropic for systematic LLM quality assurance. The platform is free for small teams; Team plans start at $200/month for larger organizations.