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AI observability 2026 Rank: #2898

Langfuse ✓

Trace, evaluate, and improve AI agents with one open platform.

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API Open Source AI Trace Management
More categories (4)
Prompt Management AI Engineering AI Evaluation AI observability
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Free + from $29/mo

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Verdict

A quick read before you dig into the full page.

Best if
Trace, evaluate, and improve AI agents with one open platform
Skip if
Complex for new users
Pick this when
Open platform

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Overview

Langfuse is an open platform engineered for the tracing, evaluation, and improvement of AI. It allows users to use production data to understand the behaviour of AI agents, collaborate on fixes, and deliver high-quality outcomes at lower costs and latency.

With features like Observability, Evaluation, and Prompt Management, Langfuse offers a fully integrated platform for AI engineering proceedings at various stages, from prototyping to delivery at production scale.

Observations facilitate monitoring of every call, tool invocation, and retrieval step, filterable by user, session, cost, latency, or custom metadata.

Evaluations can be carried out on production data or during experiments. An edge function of the platform is the ability to separate prompts from code with one-click deployments, fostering a team-based approach to improving production prompts.

Langfuse supports any language and framework that underpins OTel instrumentation, and features over a hundred integrations for ease of startup. Regardless of the scale of application or technology, from Docker Compose to Azure, Langfuse offers a flexible, efficient solution for AI engineering and trace management.

Langfuse website

Access & connections

Where you can use Langfuse, and what it plugs into.

Platforms

Web

Integrations

Docker

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Tabular

Output

  • Tabular
  • API

Pros & cons

Pros

  • Open platform
  • Supports any language
  • Observability feature
  • Evaluation feature
  • Prompt Management feature
  • Team collaboration feature
  • Operable at production scale
  • Monitor every call
Show 44 more
  • Tool invocation tracking
  • Retrieval step tracking
  • Filtering by user/session/cost/latency/metadata
  • Evaluations on production data
  • Evaluations during experiments
  • Separates prompts from code
  • One-click deployments
  • Over a hundred integrations
  • Workable on any scale
  • Supports Docker Compose
  • Supports Azure
  • Improved latency optimization
  • Cost efficiency
  • Custom Metadata feature
  • OTel Instrumentation support
  • High-quality outcomes
  • Experimental Evaluation
  • Real-time, up to 165 faster
  • Hierarchical trace capture
  • User-friendly interface
  • Datasets, experiments, evaluation integration
  • Human annotation feature
  • Cost & Latency monitoring
  • Automated alerts
  • Prompt testing on real production inputs
  • Prompt comparison models provided
  • Trace debugging
  • Generates regression datasets
  • Score configs building
  • Full cycle development
  • Open-source (MIT license)
  • Async by default
  • Production-proven
  • User-friendly installation
  • Any language/framework workability
  • Enterprise scale and security
  • Strict compliance frameworks
  • 99.9% uptime
  • Languages (via OTel) support
  • 50M+ SDK installs/month
  • 90B+ observations processed per month
  • 50, 000+ companies using Langfuse
  • Shipping velocity
  • Free tier available

Cons

  • Requires OTel instrumentation
  • May have high latency
  • Reliance on external integrations
  • Complex for new users
  • No direct model training
  • Limited trace management
  • Unclear data security features

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Releases 1

Initial release August 28, 2026 Current
Initial release of Langfuse.

FAQ 12

What is Langfuse?
Langfuse is an open-source AI engineering platform designed to aid in the tracing, evaluation, and improvement of AI. This platform enables users to collaborate on fixes, deliver high-quality outcomes at lower costs and latency, and understand the behaviour of AI agents using production data. It supports various stages of AI engineering proceedings, from prototyping to delivery at scale.
How does Langfuse work?
Langfuse works by providing a variety of features like Observability, Evaluation, and Prompt Management. Observability aids in monitoring every call, tool invocation, and retrieval step, filtered by user, session, cost, latency, or custom metadata. Evaluations can be made on production data or during experiments. The Prompt Management feature enables users to separate prompts from code using one-click deployments, promoting a team-based approach for improving production prompts.
What is the purpose of the Observability feature in Langfuse?
The Observability feature in Langfuse allows users to monitor every call, tool invocation, and retrieval step. This detailed data can be filtered based on user, session, cost, latency, or custom metadata. It provides real-time, comprehensive insight into the performance and behaviour of AI agents.
Can I conduct Evaluations on my AI during production or only during experiments using Langfuse?
Yes, Langfuse allows evaluations to be carried out both on production data and during experiments. This flexibility enhances the ability to test and improve AI agents under various conditions and in different stages of development.
What is the purpose of Prompt Management in Langfuse?
Prompt Management in Langfuse aids in separating prompts from code. It promotes a team-based approach, fostering collaboration in enhancing production prompts. It also provides the convenience of one-click deployments and rollbacks.
What benefits do one-click deployments provide in Langfuse?
One-click deployments in Langfuse offer a quick and efficient way to implement changes and improvements to AI applications. They simplify the process of separating prompts from code and foster a team-based approach to improving production prompts, enabling teams to refine and deploy AI models quickly and effectively.
Does Langfuse support other languages or frameworks?
Yes, Langfuse supports any language or framework that underpins OTel instrumentation. It is built with the flexibility to work across various coding environments, facilitating a seamless workflow irrespective of the language or framework utilized by the user.
Does Langfuse work with OTel instrumentation?
Yes, Langfuse is compatible with OTel instrumentation. Its framework is designed to underpin OTel instrumentation, demonstrating adaptability and compatibility with various tools and applications in the AI engineering space.
How does Langfuse handle different scales of application or technology?
Langfuse is engineered to handle different scales of application or technology. It offers a fully integrated platform for AI engineering proceedings at all stages, including prototyping and delivery at production scale. It provides users with a flexible and efficient solution for managing and improving AI agents, regardless of the scale of the application.
Can I use Langfuse with Docker Compose or Azure?
Yes, Langfuse works with Docker Compose and Azure, demonstrating its versatility and compatibility with a wide range of technologies. This interoperability allows it to be implemented in various environments, meeting diverse user needs and workflows.
How can Langfuse help me to reduce costs and latency?
Langfuse provides cost efficiency and latency optimization features that allow users to monitor and adjust their AI's performance for optimal results. The platform is designed to enhance performance, reduce costs and minimize latency, thus delivering high-quality outcomes more efficiently.
Can I use Langfuse to understand the behaviour of my AI agents?
Yes, Langfuse offers the functionality to use production data to understand the behaviour of your AI agents. Through detailed monitoring, tracing, and evaluative features, it provides insight into AI behaviour and performance. This facilitates the process of identifying and implementing necessary improvements.
Langfuse Free + from $29/mo
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