Braintrust
Active observability platform for AI agents with logging, automated evaluation, and continuous performance optimization in production
Overview
Braintrust is an 'active observability' platform for AI agents helping teams 'ship quality agents at scale' by capturing production patterns, converting them into evaluations, and improving quality with each deployment. Its three-part approach combines Observe (detailed tracing with real-time inspection of prompts and tool calls), Evaluate (quality standards definition, experiments on real datasets, LLM-judge scoring), and Discover (automatic pattern detection, deployment blocks on regressions). Loop Agent, the internal AI agent, automatically suggests better prompts and datasets. Pricing scales from free Starter to Pro ($249/month, includes $249 in credits, 5 GB data, 50k scores) and Enterprise custom for organizations with large volumes.
Braintrust does not provide a French-language interface and remains English-oriented. Multi-language SDKs (Python, TypeScript, Go, Ruby, C#) and REST API enable integration into any LLM stack, with a proprietary database ('Brainstore') optimized for complex agent data. The platform is SOC 2 Type II certified and supports GDPR/HIPAA, with SSO and hybrid deployments available for Enterprise customers. The per-'processed data' pricing (GB processed) and scores (with overages at $3/GB and $1.50/1k scores on Pro) offer flexibility but make costs variable depending on your agent volume. The major strength is pattern discovery and continuous optimization built in; the limitation is that the platform requires a sophisticated technical team to configure evaluations and workflows.
Our verdict
Best for teams deploying complex AI agents in production seeking a 'closed loop' of observability, evaluation, and continuous improvement with automatic problem discovery. Not for you if you have a very tight budget or a simple LLM application: Braintrust targets organizations where continuous agent improvement is a priority.