Langfuse review
A broad observability platform with open-source deployment and accessible paid tiers.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Langfuse is an open-source platform for teams building and operating LLM applications. It captures hierarchical traces for model calls, agents, tool calls, and retrieval steps, while also covering prompt versioning, evaluations, datasets, experiments, human annotation, dashboards, alerts, token usage, and model cost tracking. Developers and organizations running production LLM applications, AI agents, and workflow automation can deploy it as a managed cloud service or on customer infrastructure.
The published plans show a clear freemium path. Hobby costs $0 per month and includes all platform features with limits, 50k units per month, 30 days of data access, 2 users, and community support via GitHub. Core costs $29 per month and raises data access to 90 days, includes 100k units per month, unlimited users, and in-app support. Pro costs $199 per month and adds 3 years of data access, data retention management, unlimited annotation queues, high rate limits, and prioritized in-app support. The Teams Add-on costs $300 per month and adds enterprise SSO, SSO enforcement, fine-grained RBAC, and a dedicated Slack or Microsoft Teams support channel. Enterprise starts at $2,499 per month with audit logs, a SCIM API, custom rate limits, uptime and support SLAs, and a named lead support engineer; another Enterprise option offers custom volume pricing and vendor onboarding.
Langfuse fits teams that want broad visibility across the LLM application lifecycle rather than a narrow tracing layer. Its integrations include OpenTelemetry, Python and JavaScript/TypeScript SDKs, LangChain, LangGraph, OpenAI, Anthropic, Amazon Bedrock, Google Gemini, LiteLLM, LlamaIndex, Ragas, Zapier, and Slack. The trade-off is that retention, scale, support, and governance expand by plan, while enterprise identity controls require an additional paid tier. Choose Langfuse for open-source flexibility and coverage across tracing, evaluation, prompts, retrieval, and costs; consider another option if your needs are limited to lightweight monitoring or require enterprise controls without separate tiering.
Langfuse pros and cons
- Where it wins
- Traces agents, tools, retrieval steps, prompts, costs, and evaluations
- Supports managed cloud and self-hosted deployment
- Includes OpenTelemetry, SDK, framework, model, and workflow integrations
- Where it doesn't
- Hobby limits usage, data access, and seats
- Enterprise SSO and RBAC require the Teams Add-on
- Advanced governance and SLA features are reserved for Enterprise
Langfuse fact sheet, pricing and score →
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