Langfuse
Open source LLM engineering platform for observability, evals, and prompt management
About Langfuse
Langfuse is an open-source LLM engineering platform that helps teams collaboratively develop, monitor, evaluate, and debug AI applications. It provides comprehensive tracing, cost tracking, prompt management, and evaluation tools with native integrations for OpenAI, LangChain, LlamaIndex, and OpenTelemetry.
Pros & Cons
Pros
- Open source with self-hosting option for full data control
- Most detailed latency and cost analytics in the LLM observability market
- No per-seat pricing — unlimited users on all paid plans
- Smooth SDKs with native integrations for major LLM frameworks
- Active development with rapid feature shipping from YC-backed team
- SOC2 Type 2 and ISO27001 certified managed cloud option
Cons
- Self-hosting requires PostgreSQL, ClickHouse, Redis, and Kubernetes infrastructure
- Limited native human-in-the-loop tooling like annotation queues and review dashboards
- No built-in compliance tooling for data masking and GDPR retention workflows
- Non-technical team members cannot directly invoke AI applications for testing
- Multi-turn chatbot evaluation support is limited compared to specialized tools
Key Features
LLM Observability & Tracing
Capture detailed traces of every LLM call, retrieval step, and tool execution with timing, inputs, outputs, and metadata for full request visibility
Prompt Management
Centrally manage, version control, and collaboratively iterate on prompts with server and client-side caching to avoid added latency
Evaluations
Run LLM-as-a-judge evaluations, collect user feedback, perform manual labeling, and build custom evaluation pipelines via APIs and SDKs
LLM Playground
Test and iterate on prompts and model configurations directly, with the ability to jump from traced results into the playground for debugging
Cost & Token Tracking
Monitor usage and costs across all LLM providers with detailed breakdowns by model, trace, and time period
Datasets & Experiments
Create test datasets and run systematic experiments to benchmark prompt and model changes before deploying to production
OpenTelemetry Integration
Native OpenTelemetry support for standardized observability alongside existing application monitoring infrastructure
Self-Hosting Support
Deploy Langfuse in your own VPC or on-premises for full data sovereignty, with Docker and Kubernetes deployment options
Pricing
- 50,000 units/month
- 7-day data retention
- Community support
- No credit card required
- 100,000 units included
- 30-day data retention
- Unlimited users
- $8 per 100K overage
- 500,000 units included
- Unlimited data retention
- High rate limits
- All features
- $8 per 100K overage
- Custom units volume
- SSO & SAML
- Dedicated support
- SLA
- SOC2 & ISO27001 compliance
Best For
LLM Application Debugging
Trace and debug complex LLM chains to identify latency bottlenecks, hallucinations, and unexpected outputs in production applications
Prompt Engineering Workflows
Manage prompt versions, test variations in the playground, and evaluate quality improvements with systematic datasets and scoring
Production Monitoring & Cost Control
Track token usage, costs, and latency across LLM providers in real-time to optimize spending and maintain performance SLAs
AI Quality Assurance
Build evaluation pipelines with LLM-as-a-judge, human feedback, and custom metrics to continuously monitor and improve AI output quality
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