Braintrust
What is Braintrust?
Braintrust is an AI evaluation platform for AI engineering teams that turns production traces into repeatable evals and test cases. It combines Trace everything, Measure quality with evals, Catch issues early, and flexible versioned datasets to compare prompts and models, score outputs, and track regressions. Braintrust integrates with native SDKs, an API, and an MCP server, and is used by Notion, Dropbox, Replit, and Vercel. Plans run Starter $0/month, Pro $249/month, and Enterprise custom.
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At a glance
- Braintrust is best for AI engineering teams who need to evaluate production behavior and catch regressions before release.
- Starter $0 /mo; Pro $249 /mo; Enterprise Custom
- Yes — Braintrust offers SDKs plus an MCP server for querying logs, running evals, and updating prompts from IDEs.
What does Braintrust do?
Braintrust turns production traces into evals so teams can compare prompts and models, score outputs, and tighten quality release by release. Its workflow centers on trace inspection, evaluation runs, and prompt iteration, with features like Trace everything, Measure quality with evals, and Catch issues early helping teams move from raw logs to actionable test cases. The platform also supports custom trace views and flexible, versioned datasets so reviewers can slice behavior by environment, topic, or experiment. At scale, Braintrust is built for millions of traces quickly and hundreds to thousands of experiments, with customers like Notion, Dropbox, Replit, and Vercel using it to evaluate AI systems in production. The product includes native SDKs, an API, and an MCP server for querying logs, running evals, and updating prompts from IDEs. Enterprise plans add on-prem or hosted deployment, RBAC, custom retention and export, and compliance options such as BAA and SLA support.
Why use Braintrust?
- It connects production traces to evaluation loops, so teams can validate changes against real behavior instead of synthetic guesses.
- It supports millions of traces quickly, which helps teams inspect live systems without treating observability as a bottleneck.
- It combines automated scoring with human review, giving teams both scale and judgment when quality is ambiguous.
- It offers native SDKs and an MCP server, so developers can query logs and update prompts from their IDEs.
- Enterprise deployment options include on-prem or hosted setups, which helps privacy-sensitive teams keep tighter control over data.
Who is Braintrust for?
- AI engineers who need to turn production traces into repeatable evals and test cases.
- ML platform teams who want scalable observability across prompts, models, and experiments.
- Product teams shipping AI features who need faster feedback on quality changes.
- Engineering leaders who need governance, retention controls, and deployment flexibility for AI systems.
What are Braintrust's key features?
Trace everything
Capture every prompt, response, and span across millions of traces quickly, so teams can debug production behavior and compare runs without missing context.
Measure quality with evals
Run evals with automated and human scoring, plus 10,000+ tests in a full eval suite, to track quality changes before shipping.
Catch issues early
Use live performance monitoring and automations and alerts to spot regressions fast, helping teams respond before bad outputs reach users.
Scalable trace ingestion
Ingest millions of traces quickly with OpenTelemetry support, so high-volume AI systems stay observable without slowing down logging or analysis.
Flexible, versioned datasets
Build versioned datasets from traces and experiments, then reuse them for evals and prompt work to keep tests tied to real production data.
Native SDKs
Work from SDKs and the Braintrust MCP server to query logs, run evals, and update prompts from IDEs like Cursor and VS Code.
Hybrid deployment
Deploy on-prem or hosted with RBAC, custom data retention, and S3 data export, which helps privacy-sensitive teams control where data lives.
Secure by default
Support enterprise controls like RBAC, custom policies, BAA, and uptime SLA, giving regulated teams clearer governance and support options.
What does Braintrust integrate with?
- Cursor
- Claude Code
- Windsurf
- Cline
- GitHub Copilot
- Gemini
- Anthropic
- OpenAI
- OpenRouter
- OpenTelemetry
- Vercel AI SDK
- Claude Agent SDK
- OpenAI Agents SDK
- LlamaIndex
- CrewAI
- AgentScope
- LangChain
- LangSmith
- LangGraph
- Agno
- Apollo GraphQL
- Autogen
- AWS Bedrock
- Azure AI Foundry
- Baseten
- Braintrust MCP
- Cerebras
- Claude Desktop
- Cloudflare Workers AI
- CloudWeGo Eino
What are Braintrust's use cases?
AI engineers turn traces into tests
AI engineers who need to turn production traces into repeatable evals and test cases use Braintrust to capture real failures with Trace everything and convert them into Flexible, versioned datasets. They then Measure quality with evals to compare prompt or model changes before shipping, so regressions are caught before users feel them.
Platform observability across experiments
ML platform teams use Braintrust to centralize prompts, models, and experiments with Scalable trace ingestion and Customizable trace views. That gives them one place to inspect millions of traces quickly, spot drift across releases, and keep observability usable as usage grows.
Product feedback for AI releases
Product teams shipping AI features use Braintrust to Catch issues early when a new prompt or model changes output quality. With Live performance monitoring and Automations and alerts, they can see quality drops sooner, route them to the right owners, and protect launch timelines.
Governed deployment for AI systems
Engineering leaders use Braintrust to keep AI systems secure and deployable across environments with Hybrid deployment and Secure by default. They can retain the controls they need while still giving teams access to observability and eval workflows that support faster, safer releases.
How does Braintrust work?
- Connect your first app, model, or prompt source with Native SDKs or Braintrust MCP, then start Trace everything so production interactions flow into one workspace for analysis.
- Organize those traces into Flexible, versioned datasets, then use Trace to dataset to turn real failures into reusable test cases and benchmark sets.
- Run Measure quality with evals using Automated and human scoring, comparing prompt, model, or experiment changes before they reach users.
- Set up Live performance monitoring and Automations and alerts so quality drops, latency spikes, or broken outputs surface quickly to the right team.
- Refine prompts and workflows in Fast prompt engineering, then review results in Customizable trace views and keep improving with the next eval cycle.
How much does Braintrust cost?
Starter
$0 / month- 1 GB processed data
- + $4/GB
- 10k scores
- + $2.50/1k
- 14 days retention
- Unlimited users, projects, datasets, playgrounds and experiments
Pro
$249 / month- 5 GB processed data
- + $3/GB
- 50k scores
- + $1.50/1k
- 30 days retention
- Custom topics, charts, environments and priority support
Enterprise
Custom pricing- Custom policies
- S3 data export
- Custom
- Business associate agreement (BAA)
- Uptime service level agreement (SLA)
- Shared Slack channel
- Guaranteed service level agreements (SLAs)
Frequently asked questions
What is Braintrust?
Braintrust is an AI evaluation platform for AI engineering teams that turns production traces into repeatable evals and test cases. It combines Trace everything, Measure quality with evals, Catch issues early, and flexible versioned datasets to compare prompts and models, score outputs, and track regressions. Braintrust integrates with native SDKs, an API, and an MCP server, and is used by Notion, Dropbox, Replit, and Vercel. Plans run Starter $0/month, Pro $249/month, and Enterprise custom.
How much does Braintrust cost? Is it free?
Braintrust has a free plan, with paid tiers including Pro at $249 / month, Enterprise at Custom pricing.
What is Braintrust used for? Who is it for?
Braintrust is used for Trace everything, Measure quality with evals, and Catch issues early. It's built for AI engineers, ML platform teams, and Product teams shipping AI features.
Does Braintrust have an API and what does it integrate with?
Braintrust offers SDKs plus an MCP server for querying logs, running evals, and updating prompts from IDEs. It integrates with Cursor, Claude Code, Windsurf, Cline, GitHub Copilot, and 25 more.
Editor's read
Check the Starter and Pro usage ceilings before rollout: Starter includes 1 GB processed data, 10k scores, and 14 days retention, while Pro raises that to 5 GB, 50k scores, and 30 days. If your trace volume or retention needs exceed those limits, Enterprise is the tier that adds custom retention and export.
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