Keywords AI

Langfuse vs Patronus AI

Compare Langfuse and Patronus AI side by side. Both are tools in the Observability, Prompts & Evals category.

Quick Comparison

	Langfuse	Patronus AI
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Open Source	Enterprise
Best For	Teams who want open-source LLM observability they can self-host and customize	AI teams that need rigorous, automated quality evaluation and safety testing
Website	langfuse.com	patronus.ai
Key Features	Open-source LLM observability Detailed trace and span tracking Prompt management Evaluation scoring Self-hosted and cloud options	Automated LLM evaluation platform Hallucination detection RAG-specific evaluation metrics Red-teaming capabilities CI/CD integration
Use Cases	Self-hosted LLM monitoring Open-source tracing for AI applications Prompt versioning and management Cost tracking across providers Community-driven observability	Detecting hallucinations in production RAG quality evaluation Adversarial testing of LLM systems Continuous evaluation in CI/CD Model comparison and selection

When to Choose Langfuse vs Patronus AI

Choose Langfuse if you need

Self-hosted LLM monitoring
Open-source tracing for AI applications
Prompt versioning and management

Pricing: Open Source

Choose Patronus AI if you need

Detecting hallucinations in production
RAG quality evaluation
Adversarial testing of LLM systems

Pricing: Enterprise

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.

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About Patronus AI

Patronus AI provides automated evaluation and testing for LLM applications. The platform detects hallucinations, toxicity, data leakage, and other failure modes using specialized evaluator models. Patronus offers pre-built evaluators for common use cases and supports custom evaluation criteria, helping enterprises ensure AI safety and quality before and after deployment.

View Patronus AI profile →Visit website

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 →