Keywords AI
Langfuse vs Traceloop
Compare Langfuse and Traceloop side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Open Source | open-source |
| Best For | Teams who want open-source LLM observability they can self-host and customize | Teams already using Datadog/Splunk wanting LLM observability |
| Website | langfuse.com | traceloop.com |
| Key Features |
|
|
| Use Cases |
| — |
When to Choose Langfuse vs Traceloop
- Self-hosted LLM monitoring
- Open-source tracing for AI applications
- Prompt versioning and management
About Langfuse
Langfuse is an open-source LLM observability platform that provides tracing, analytics, prompt management, and evaluation for AI applications. It captures detailed traces of LLM calls, supports custom scoring, and integrates with LangChain, LlamaIndex, Vercel AI SDK, and raw API calls. Langfuse can be self-hosted for data privacy or used as a managed cloud service. Its open-source model and generous free tier make it popular with startups and developers.
About Traceloop
The OpenTelemetry standard for AI. Pipes LLM telemetry into Datadog, Splunk, or any OTel backend.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evals tools →