Braintrust
Trace, evaluate, and discover patterns in AI agents. Ship quality agents at scale with real-time observability, evals, and automatic pattern discovery.
Editor's Verdict
Key Takeaways
- Trace everything
- Evaluate with evals
- Discover patterns automatically
- Observability
In-Depth Review: What is Braintrust?
Braintrust is the leading AI observability and evaluation platform designed for teams building agents in production. It provides real-time tracing of agent traces, prompt and tool call inspection, and performance monitoring. With built-in evals, teams can define quality metrics, run experiments, and score outputs using LLMs, code, or humans. The platform's discovery engine automatically surfaces patterns in production data, enabling continuous improvement. Trusted by top AI teams like Coursera, Notion, and Graphite, Braintrust helps catch regressions, block bad releases, and optimize agent quality at scale.
Core Features
Trace everything
Inspect prompts, responses, and tool calls in real time with scalable agent trace ingestion.
Evaluate with evals
Score outputs using LLMs, code, or humans; run experiments against versioned datasets.
Discover patterns automatically
Topics surfaces patterns in real time across tasks, issues, and sentiment for continuous improvement.
Observability
Live performance monitoring, custom views, and annotation across millions of logs.
Loop Agent
AI that helps you optimize agents by generating better prompts, scorers, and datasets automatically.
Custom facets
Define business dimensions like use case or compliance; Topics clusters traces accordingly.
Task-specific trace views
Build annotation interfaces for different workflows without frontend work.
Trace to dataset
Turn production traces into eval datasets with one click for regression testing.
MCP integration
Query logs, run evals, and update prompts directly from your IDE via MCP server.
Framework agnostic
Works with any stack and provides native SDKs for Python, TypeScript, Go, Ruby, C#, and more.
Brainstore database
Database built for AI data at scale, offering faster search, write latency, and span load times.
Security and compliance
SOC 2 Type II, GDPR, HIPAA compliant with SSO, RBAC, and hybrid deployment options.
Pricing
Starter
- $10 credits included for Topics
- 1 GB processed data (additional $4/GB)
- 10k scores (additional $2.50/1k)
- 14-day data retention
- Unlimited users, projects, datasets, playgrounds, experiments
- Human review scores (1 per project)
- Unlimited saved table views, custom columns, custom trace views
- Community support
Pro
- $249 credits included for Topics
- 5 GB processed data (additional $3/GB)
- 50k scores (additional $1.50/1k)
- 30-day data retention (additional $0.50/GB/mo)
- Unlimited users, projects, datasets, playgrounds, experiments
- Unlimited human review scores
- Custom charts, environments, RBAC (basic roles)
- Priority support, shared Slack channel
Enterprise
- Custom data retention and export
- RBAC with custom roles
- Premium support with on-prem or hosted deployment
- SAML single sign-on (SSO)
- HIPAA compliance
- Uptime SLA
- Guaranteed SLAs
- Custom policies and S3 export
Pros and Cons
Pros
- Deep observability for agentsProvides real-time visibility into agent behavior, including prompts, responses, and tool calls.
- Automatic pattern discoveryTopics surfaces unknown patterns in production, turning them into actionable evals.
- Integrated evaluation platformCombines tracing, evals, and discovery in one place for the whole team.
- Scalable and fastBrainstore database handles complex agent traces at scale with faster search and query times.
- Enterprise-grade securitySOC 2, GDPR, HIPAA compliant with SSO, RBAC, and hybrid deployment.
Cons
- Limited free tier data retentionStarter plan has only 14-day retention, which may be insufficient for long-term analysis.
- Costly at high volumeAdditional processed data and scores can become expensive for large-scale deployments.
- Learning curve for setupIntegrating SDKs and configuring custom facets may require initial effort.
- No on-prem in lower plansHybrid deployment is only available in Enterprise plan, limiting data sovereignty for Pro users.
- Limited community supportStarter plan only includes community support, which might be slow for critical issues.
Use Cases & Recommended Professions
AI/ML Engineer→ View Toolkit
Needs to monitor and evaluate LLM agents in production to catch regressions and improve quality.
Product Manager (AI)→ View Toolkit
Uses Braintrust to track agent behavior and align evaluations with business metrics.
VP of Engineering→ View Toolkit
Requires a platform to scale AI observability across teams and ensure reliable releases.
Data Scientist→ View Toolkit
Leverages evals and pattern discovery to analyze agent outputs and optimize performance.
CTO→ View Toolkit
Seeks robust observability to maintain trust in AI systems and comply with security standards.
Software Engineer→ View Toolkit
Integrates SDKs to instrument agent traces and uses MCP to debug from IDE.
Frequently Asked Questions
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ℹ️ Curation Disclosure: The overview and features of Braintrust were synthesized using AI and fact-checked by our curation team to ensure accuracy.
