Braintrust
App : A product you use directly
Evaluation and logging platform for AI products, oriented towards product teams.
Very strong on evals, hosted only.
Security reflects where data goes, requested permissions and incidents on record at the verification date. It is not a guarantee of zero risk: check the deployment mode and the connections you enable.
What it does, concretely
Teams building AI agents struggle to understand what actually happens in production: failures are silent, regressions hard to spot, and standard logs fall short when it comes to inspecting complex agent traces. Braintrust addresses this need with an active observability platform built specifically for agents.
The platform rests on three pillars: real-time trace observation (prompts, responses, tool calls, latency, cost), output evaluation through versioned datasets and automated or human scoring, and pattern discovery across production logs using natural language investigation. A module called Loop automatically generates better prompts, scorers, and datasets from a plain-language description of what you want to optimize.
Braintrust targets product and engineering teams running agents in production, from startups to large enterprises. Customers such as Notion, Coursera, and Graphite use it to iterate quickly on their models and catch issues before they reach end users.
The platform is not suited for individual or exploratory use without a production context: it assumes an active AI project, meaningful trace volumes, and a team ready to instrument their code using the provided SDKs.
What it offers
- ·Real-time inspection of every agent trace: prompts, responses, tool calls, latency, and cost.
- ·Output scoring by LLMs, code, or humans, with side-by-side prompt and model comparison.
- ·Versioned datasets built in one click from production traces, to create regression tests from real failures.
- ·Automatic pattern discovery across logs through natural language investigation and topic classification.
- ·Loop module: automatic generation of optimized prompts, scorers, and datasets from a plain-language objective.
- ·MCP server to query logs, run evals, and update prompts directly from your IDE.
- ·Customizable annotation views per task type, with no frontend development required.
- ·Hybrid deployment to host the Brainstore data plane on your own infrastructure. (paid)
In practice
- Price
- Freemium
- Commercial use
- Commercial use: yes
- Available on
- web
Security and data
- Rating
- Security: nothing to flag
- Your data
- Data with the vendor
- Maintenance
- Active
Links and repository checked on 25 October 2026 · added on 1 September 2023