Directory/Analytics/AI Engineering/Langfuse
Langfuse

Langfuse

Langfuse is an open-source AI engineering platform for building, monitoring, and improving LLM applications. It provides end-to-end tracing of LLM calls, tool invocations, and retrieval steps, along with prompt management, automated evaluations (LLM-as-a-judge, heuristics, human review), experiments, and cost/latency dashboards. Designed for engineers and AI teams, it integrates with 100+ tools and frameworks, supports OpenTelemetry, and can be self-hosted or used via cloud. Trusted by Fortune 50 companies, it processes billions of observations monthly.

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Added on
Jul 13, 2026
Monthly Visits
14.1K
TracingEvaluationPrompt ManagementPlaygroundExperimentsHuman AnnotationCost & LatencyOpen source (MIT)OTel native100+ integrations
Product information

Everything worth knowing about Langfuse

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Observability
Hierarchical traces capture every LLM call, tool invocation, and retrieval step. Filter by user, session, cost, latency, or custom metadata.
Evaluation
LLM-as-a-judge, heuristic functions, or human review. Run evaluators on production data or during experiments.
Prompt Management
Separate prompts from code with one-click deployments and rollbacks.
Playground
Test prompts on real production inputs and compare models side-by-side.
Cost & Latency
Monitor cost, latency, and quality with dashboards and automated alerts.
Technical capabilities
ClickHouse OLAP Database
ClickHouse OLAP backend enables fast queries on millions of traces.
Async Ingestion
Async ingestion via Redis queue ensures tracing never blocks application.
Must watch videos
LLM Observability with Langfuse: Debugging a Broken RAG Agent
3:59
Tutorial3:59
LLM Observability with Langfuse: Debugging a Broken RAG Agent
I debug a RAG support agent that gives a confident, wrong answer, tracing the failure step by step in Langfuse until I find the exact bug (a bad entry in a routing table) and fix it. 🔗 Try Langfuse: https://langfuse.com
Add Full Observability to Your OpenClaw Agent with Langfuse
3:50
Tutorial3:50
Add Full Observability to Your OpenClaw Agent with Langfuse
See exactly what your OpenClaw agent is doing, every model call, tool run, and cost, in real time. Install the official Langfuse plugin and get full visibility into your agent's behavior with just a couple of commands. 🔗 Plugin: https://clawhub.ai/codecls/plugins/openclaw-x-langfuse-plugin 🔗 Langfuse: https://langfuse.com/integrations/other/openclaw
Integrating Slack with Langfuse
1:24
Tutorial1:24
Integrating Slack with Langfuse
Stop finding out about production issues after your users do. In this video, you'll learn how to connect Slack to Langfuse so your team gets automatic alerts the moment important metrics — like latency, cost, or quality scores — move outside their expected ranges. We walk through the setup, from connecting your Slack workspace to configuring alerts that fire when something needs your attention, so your team can act fast instead of digging through dashboards.

Who uses it

Real use cases, no hype
Observability
Hierarchical traces capture every LLM call, tool invocation, and retrieval step.
Evaluation
LLM-as-a-judge, heuristic functions, or human review to assess output quality.
Prompt Management
Separate prompts from code with one-click deployments and rollbacks.
Playground
Test prompts on real production inputs and compare models side-by-side.
Experiments
Define test cases and run experiments; compare results side by side.
Human Annotation
Collaborative human-in-the-loop workflows to review traces and create golden datasets.
Cost & Latency
Monitor cost, latency, and quality with dashboards and automated alerts.
What's great
  • Open source with MIT license
  • 100+ integrations with major frameworks
  • Free tier with 50k observations per month
  • Built-in cost and latency dashboards
Technical strengths
  • Clickhouse backend for millisecond trace queries
  • Async tracing never blocks application code
Where it falls short
  • Free tier limited to 50k observations monthly
  • Self-hosting requires Docker or Kubernetes expertise
  • Some advanced features require cloud subscription
  • UI can become sluggish with tens of thousands of traces
Technical limitations
  • Complex analytical queries can overload Clickhouse
  • Alerting and notification options are limited
For technical folks

The deep-dive specs

Architecture
ClickHouse OLAP Database
Ingestion
Async via Redis Queue
Storage
S3/Blob Storage
Compliance
SOC 2, ISO 27001, GDPR, HIPAA
Uptime
99.9% uptime guarantee

FAQ

Includes technical Q&A
Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, and analytics for LLM applications.

Traffic Insights

Monthly Visits

14.1K

September 2026

Growth Rate

+14,6%

vs last month

Dominance

0%

in Analytics

Top Country

—

Top Countries Breakdown

—

Growth Trend

Rising

Consistent user growth over last 6 months.

Honest pricing

No sneaky tiers, no “contact sales”

Here's who each plan is actually for — and where the hidden charges might hit.

Free
Free

Individuals

  • 50k observations/month
  • 1 project
  • 1 member
  • Community support
Team
Most picked
$59/mo

Teams

  • 500k observations/month
  • Unlimited projects
  • Unlimited members
  • Priority support
  • All features
Enterprise
Custom

Enterprise

  • Custom observations
  • Unlimited projects
  • Unlimited members
  • SSO/SAML
  • SLA
  • Dedicated support
  • HIPAA compliance
See full feature comparison
Reviews

What the internet actually thinks

Data refreshed weekly. No paid placements.

Trustpilot
Not reviewed yet
G2
G2
Not reviewed yet
C
Capterra
Not reviewed yet
Product Hunt
Not reviewed yet
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