Privacy-first search infrastructure for AI agents, with smart routing, structured results, and native API, MCP, and Skill access.
Freemium
Summary
Evaluation-first AI development — measure whether a prompt or model change actually improved anything.
Description
Braintrust is built around the discipline that separates working AI products from demos: evaluation. Instead of shipping a prompt change and hoping, you run it against a dataset and see whether scores moved.
The workflow
- Collect data. Log production traces, or curate examples by hand.
- Build datasets from the cases that matter, including the failures.
- Write scorers — code-based assertions, model-graded rubrics, or human review.
- Run experiments comparing prompts, models, and retrieval strategies side by side.
- Compare and ship with a diff view showing which examples improved and which regressed.
Supporting features
- Playground for iterating on prompts against real data rather than one cherry-picked example
- Tracing with full observability over agent runs
- Human review queues for cases automated scoring cannot judge
- CI integration, so evaluations gate deploys the way tests do
Fit
Best for teams past the prototype stage who have felt the pain of a "small prompt tweak" breaking something quietly. Free tier for individuals and small projects, usage-based paid plans, and self-hosted enterprise deployment for sensitive data.
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