Langfuse

Open-source LLM observability

Observability Free self-host / cloud from $0
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What It Is

Langfuse is the leading open-source LLM observability platform. It provides tracing, prompt management, evals, datasets, and usage analytics — all with a self-hostable option for teams that need data residency or air-gapped deployments. Framework-agnostic: works with LangChain, LlamaIndex, Instructor, or raw API calls.

How It Works

Add the Langfuse SDK to your app and wrap LLM calls with a decorator or use their auto-instrumentation. Every trace is captured with structured metadata. The dashboard provides filtering, aggregation, and drill-down. Prompt management lets you version prompts and deploy them without redeploying code. Evals can run LLM-as-judge or custom Python functions against datasets.

Pricing Breakdown

Self-host: free, MIT licensed. Cloud: Free tier (50k observations/month), Pro $59/month, Team custom. Dedicated hosting available for enterprise.

Who Uses It

Teams needing self-hosting, compliance-sensitive deployments, and framework-agnostic observability. Popular in European and regulated industries.

Strengths & Weaknesses

✓ Strengths

  • Open source (MIT)
  • Framework-agnostic
  • Self-hostable
  • Rich dashboard

× Weaknesses

  • Less polished than LangSmith
  • Self-host setup required
  • Smaller community

Best Use Cases

Self-hosted observabilityCompliance-sensitive deploysMulti-frameworkCost tracking

Alternatives

LangSmith
LangChain's observability platform
Helicone
LLM observability via proxy
Arize Phoenix
Open-source ML observability
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