Braintrust vs Galileo

Detailed side-by-side comparison to help you choose the right tool

Braintrust

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AI evaluation

Braintrust provides ai evaluation capabilities for teams building and operating AI applications. It supports the MCP ecosystem.

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Starting Price

Free

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AI evaluation

Galileo provides ai evaluation capabilities for teams building and operating AI applications.

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Starting Price

Custom

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Feature	Braintrust	Galileo
Category	AI evaluation	AI evaluation
Pricing Plans	340 tiers	285 tiers
Starting Price	Free
Key Features	• Workflow Runtime • Tool and API Connectivity • State and Context Handling	• Automated hallucination detection using proprietary ChainPoll methodology • Real-time production monitoring for LLM applications with custom alerting • RAG pipeline evaluation covering both retrieval and generation quality

✓Connects datasets, experiments, prompts, and production traces in one workflow
✓Python and TypeScript SDKs support code scorers and model-based judges
✓Side-by-side experiments make regressions visible before deployment
✓OpenTelemetry and major model-provider integrations reduce instrumentation work

✗The staged $249/month Pro price needs manual verification
✗LLM-as-judge scores still require calibration against human decisions
✗Teams must design representative datasets; the platform cannot supply product-specific truth
✗A full-stack platform can be more than a small prototype needs

✓Luna evaluators are dramatically cheaper than LLM-as-judge — eval coverage can stay on in production
✓End-to-end coverage: evals + traces + guardrails + agent root-cause from one vendor
✓Strong enterprise compliance posture (VPC, audit, SSO) suitable for regulated industries

✗No public pricing — every conversation starts with sales, which slows POC adoption
✗Heavier and more opinionated than open-source [/tools/langfuse](/tools/langfuse) or [/tools/arize-phoenix](/tools/arize-phoenix) — early-stage teams may find it overkill
✗Luna evaluators are proprietary — verify quality on your domain before assuming they replace LLM-judge in your stack

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