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Braintrust

observability
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Braintrust is an LLM observability and evaluation platform that treats AI quality as a release-level concern — combining production tracing, CI-integrated evaluation, prompt experimentation, and statistical regression detection in a single platform. It's the most evaluation-forward LangSmith alternative for teams that want to gate deployments on quality scores.

The Core Idea

Most observability tools tell you what happened. Braintrust closes the loop: it captures traces, runs evaluations against them, and lets you block releases in CI if quality regresses. The workflow mirrors how mature engineering teams treat test coverage — not as a dashboard to check, but as a gate in the deployment pipeline.

Key Capabilities

  • Production tracing: Full spans across multi-step LLM workflows — inputs, outputs, tool calls, metadata, and cost. Live request flows with drill-down into individual traces
  • Experiment runner: Compare prompts side-by-side against datasets, score with LLMs, code, or humans, and catch regressions before they ship
  • CI integration: Run eval suites in CI and fail the build if pass rates drop — the same way unit tests work
  • Brainstore: Purpose-built storage for AI observability — query millions of traces quickly
  • AI-assisted iteration: Built-in agent that can generate test cases, run evaluations, and iterate on prompts autonomously

Getting Started

pip install braintrust

import braintrust

tracer = braintrust.init_logger(project="my-agent")

with tracer.start_span("llm-call") as span:
    result = client.messages.create(...)
    span.log(input=prompt, output=result.content[0].text)

Pricing

Tier Spans Eval runs Retention
Free 1M 10k 14 days
Pro Unlimited Unlimited 1 month
Enterprise Custom Custom Custom

Pro is $249/month. SOC 2 Type II, GDPR compliant, HIPAA available.

Key Characteristics

Property Value
License Proprietary SaaS
Provider Braintrust Data, Inc.
Website braintrust.dev
Docs braintrust.dev/docs

Further Reading