Braintrust | AI Observability & Evals for Agent Traces — 2026 Guide

Trace everything in real time

Inspect prompts, responses, and tool calls in real time. Search across millions of logs and track latency, cost, and quality as your agents run in production.

See what actually happened in production and catch issues early

Score outputs with LLMs, code, or humans

Run experiments against real datasets, compare prompts and models side-by-side, and score outputs with LLMs, code, or humans using flexible, versioned datasets.

Define what good looks like before you ship and block bad releases

Find recurring behaviors in production traces

Patterns is an automation that identifies recurring issues and opportunities across production traces, with natural language trace investigation, topic classification at scale, and failure diagnosis from traces.

Understand agent behavior and improve quality at scale

AI that helps you improve agents

Describe what you want to optimize, and Loop generates better prompts, scorers, and datasets automatically. It can run evaluations, generate test cases, and iterate on prompts autonomously.

Optimize your evals without manual scanning

Turn production traces into eval datasets

Build regression tests from real failures and edge cases with one click, instead of relying on synthetic examples. Build annotation interfaces that match your team's workflow with no frontend work required.

Test what ships against real-world data

Secure by default, compliant from day one

SOC 2 Type II certified and GDPR compliant, with SSO/SAML, RBAC, HIPAA compliance, granular permissions at the project and resource level, and hybrid deployment options.

Meet enterprise security requirements out of the box

• Comprehensive observability for agentsBraintrust provides active observability for AI agents, allowing you to inspect every trace, prompt, response, and tool call in real time. It scales to millions of logs and tracks latency, cost, and quality, with custom views and annotation capabilities.
• Built-in evaluation and discoveryThe platform includes evals for defining quality, scoring with LLMs, code, or humans, and discovery features like Topics that automatically surface patterns in production. You can turn production traces into datasets with one click and block bad releases with quality gates.
• Framework agnostic with native SDKsBraintrust works with any stack you already use, offering native SDKs for Python, TypeScript, Go, Ruby, C#, and more. It also provides an MCP server to connect your coding agent to your AI stack, with no framework lock-in or rewrites.
• Secure and compliant by defaultBraintrust is SOC 2 Type II certified, GDPR compliant, and offers SSO/SAML, RBAC, HIPAA compliance, and hybrid deployment options. It includes granular permissions and a trust center for enterprise-grade security.

• Pricing tiers and free usageBraintrust offers a free Starter plan with $10 monthly credits, 1 GB processed data, 10k scores, and 14-day retention. The Pro plan costs $249/month with more credits and features, while Enterprise has custom pricing. No credit card is required to start, and qualifying startups get 6–12 months free on Pro.
• Data retention and export optionsStarter includes 14-day retention, Pro includes 30-day retention with optional extended retention at $0.50/GB/month, and Enterprise offers custom retention and export. S3 data export is available only on Enterprise plans.
• Model credits and token ratesMonthly model credits cover AI features like Topics and built-in models. Starter includes $10 credits, Pro includes $249 credits, and Enterprise is custom. After credits are used, token rates apply, but specific rates are not shown on the pricing page.
• Customization and enterprise featuresCustom charts, environments, and RBAC are available on Pro and Enterprise, but not on Starter. Enterprise adds custom policies, S3 export, and premium support with on-prem or hosted deployment. Human review scores are limited to 1 per project on Starter, unlimited on Pro and Enterprise.

Debug failing agent runs in production

When an agent misbehaves, Braintrust lets you inspect every trace, prompt, response, and tool call in real time. Search across millions of logs, track latency, cost, and quality, and use Nitro, Brainstore's query engine, to retrieve the latest matches and count phrases faster than competing tools. This makes it possible to find the root cause of a failure without manually scanning raw logs.

Turn production failures into regression tests

Braintrust can convert real production traces into eval datasets with one click, so you build regression tests from actual failures and edge cases instead of synthetic examples. Teams then run experiments against those datasets, compare prompts and models side-by-side, and score outputs with LLMs, code, or humans before shipping. This is the workflow Notion uses to evaluate AI at scale across 70 engineers.

Catch recurring agent issues before release

Patterns is an automation that identifies recurring issues and opportunities across production traces. It surfaces recurring behavior worth investigating, applies natural language trace investigation, and provides evidence-backed pattern discovery so teams can verify the evidence, test an improvement, and measure the result in one system. Graphite used this approach to achieve a 5% reduction in negative rules for its AI code review.

Optimize prompts and evals with an AI agent

Loop is Braintrust's built-in AI agent that helps improve agents. You describe what you want to optimize, and Loop generates better prompts, scorers, and datasets automatically. It can run evaluations, generate test cases, and iterate on prompts autonomously, which Allen Kleiner, AI Engineering Lead, says helps teams understand trace details that would be impossible to scan manually.

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