Braintrust is a platform for evaluating and observing AI apps and agents, used to trace production runs and score outputs before and after release.
In plain words
Braintrust traces prompts, responses and tool calls as they happen. Its evaluations have three parts: data, the examples you test on; a task, such as one model call or a multi-step agent; and evaluators, which score or label the results. Scoring can use LLMs, code or people. Teams run this on datasets during development and on real traffic in production to catch regressions.
A quick example
Imagine a team switching their assistant to a new model. They run their saved dataset of tricky questions through both versions in Braintrust, compare the scores, and block the release if the new model does worse on any key check.
Where you'll meet it
- Evaluating prompt and model changes before release.
- Monitoring agent quality in production.
Related
Sources
- DocsEvaluate systematically, Braintrust documentation · read 29 Sept 2026
- DocsBraintrust, Braintrust · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.