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What is Langfuse?
Langfuse is an open-source AI engineering platform designed to assist teams in building, monitoring, and enhancing their large language model (LLM) applications. Founded in 2023, it has rapidly gained traction, serving over 100,000 engineers and processing more than 90 billion observations monthly. The platform integrates observability, evaluation, prompt management, and analytics into a unified workflow, enabling developers to trace LLM calls, manage prompts, evaluate model performance, and analyze metrics such as cost and latency. Langfuse is compatible with various programming languages and frameworks, including Python, TypeScript, Go, Java, and .NET, and supports numerous agent frameworks like LangChain and Vercel AI SDK. Its versatility makes it suitable for a wide range of users, from startups to large enterprises, facilitating the development and optimization of AI applications across diverse industries.
AI Tool Review Summary
4.6/5
High, consistent, and on-brand
Clean and minimal
LLMNLP
To provide comprehensive observability and evaluation tools for LLM applications
Supports multiple programming languages and frameworks, including Python, TypeScript, Go, Java, and .NET
Subscription-based pricing with a free tier
Features with the highest value for users are highlighted here.
Hierarchical tracing of LLM calls
Prompt versioning
LLM-as-a-judge evaluations
Cost and latency monitoring
AI developers
Data scientists
Product managers
DevOps engineers
Startups
Large enterprises
Research teams
Quality assurance teams
Consultants
Educators
Free
$0/free
50,000 units per month 30-day data retention
Popular
Core
$29/monthly
100,000 units per month 90-day data retention
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
Pros & Cons
Comprehensive observability and evaluation tools for LLM applications. Flexible deployment options, including self-hosting and managed services.
Newer platform with a smaller community compared to established tools. Some features may feel early-stage, especially under complex workflows or high traffic.
FAQs
Just Launched
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Rating
5.0
Pros
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