Braintrust

Braintrust is an evaluation and observability platform for building reliable AI applications, helping teams systematically test, measure and improve the quality of their LLM-powered products. As companies move generative AI from impressive demos into production, they hit a hard truth: AI outputs are non-deterministic and hard to evaluate, and without rigorous testing it's nearly impossible to know whether a prompt change, model swap or new feature makes things better or worse. Braintrust brings the discipline of evaluation and experimentation to AI development.

At its core, Braintrust lets teams define evaluations — datasets of inputs with criteria or expected outputs — and run their AI against them to score quality objectively and repeatably. This means you can experiment with prompts, models and logic, then measure the impact with real data rather than gut feel, catching regressions before they reach users and steadily improving performance. It supports a range of scoring methods, including using AI to grade outputs, and makes it easy to compare versions side by side, turning AI development from guesswork into an iterative, measurable engineering process.

Beyond evaluation, Braintrust provides logging and observability for AI in production, so teams can monitor real-world behavior, capture interesting or problematic cases, and feed them back into their evaluation sets — closing the loop between production and improvement. This makes it a central tool for serious AI teams who treat quality and reliability as first-class concerns. It's used by companies building AI features that must work consistently, where the cost of poor or unpredictable outputs is high. As evaluating and trusting AI becomes one of the defining challenges of shipping generative AI, platforms like Braintrust are increasingly essential. For teams that want to build AI applications they can actually trust — and to measure and improve them rigorously — Braintrust offers a powerful, purpose-built evaluation and observability solution.