Braintrust is the active observability platform for AI agents, combining production trace monitoring, rigorous evals and pattern discovery in one workspace shared by engineering and product teams. (★ 4.5 on G2)
Braintrust starts from a conviction that evaluation, not logging, is the core activity of shipping good AI. Its evals workflow lets you define what ‘good’ looks like before you ship: build versioned datasets, run experiments comparing prompts and models side by side, and score outputs automatically with LLM judges, code-based scorers or human reviewers. One-click conversion turns any production trace into an eval test case, so the failures your users actually hit become your regression suite.
In production, Braintrust ingests every agent trace and tool call into Brainstore, a database purpose-built for AI data, and lets you search millions of logs in natural language while tracking latency, cost and quality live. The Discovery layer applies intelligence to those traces to surface recurring behaviors and failure modes with supporting evidence, so teams can verify, test an improvement and measure the result without leaving the platform. Framework-agnostic SDKs cover Python, TypeScript, Go, Ruby and C#, and the UI is designed so product managers and domain experts can review quality alongside engineers.
The Starter tier is free and includes 1 GB of processed data per month and 10,000 scores with unlimited users ($4/GB and $2.50 per 1,000 scores after that). Pro costs $249/month with 5 GB of data, 50,000 scores and 30-day retention, and Enterprise is custom with private deployment options and compliance agreements. Every plan includes model credits for LLM-as-judge scoring before token rates apply.
Product and engineering teams whose main loop is changing a prompt, running an eval and comparing scores before every release. Solo developers should know the jump from free to Pro is steep — self-hosted open-source alternatives exist for leaner budgets.