Braintrust is an evaluation-first platform for LLM application development that treats AI quality as a measurable, improvable metric. Rather than deploying and hoping, teams use Braintrust to systematically test and improve their AI applications before and after deployment.
The prompt playground enables rapid iteration on prompts with side-by-side comparison across different models and configurations. Changes can be tested immediately against curated datasets to measure impact on quality metrics.
Automated evaluation supports custom scoring functions, LLM-as-judge evaluators, and programmatic checks. Datasets are built from production data, manually curated examples, or synthetically generated test cases. CI/CD integration adds quality gates to deployment pipelines.
Detailed tracing captures every step of LLM application execution for debugging. The platform integrates with any LLM provider and framework through Python and JavaScript SDKs.