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Langfuse

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uuid0000b4o

Namestring
Langfuse
Legal namestring
Langfuse GmbH
Websiteurl
langfuse.com
Company typeenum
Private
Founded yearint
2022
Descriptiontext

Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, metrics, and human annotation for production LLM and AI agent applications. The platform captures hierarchical traces of every LLM call, tool invocation, and retrieval step via OpenTelemetry-native instrumentation and stores them on a ClickHouse OLAP backend with PostgreSQL for transactional state, Redis/Valkey for async ingestion, and S3-compatible blob storage for large multi-modal payloads, enabling millisecond analytics across millions of traces at a reported 10B+ observations per month. Its product surface includes an LLM Observability module, version-controlled Prompt Management with one-click deployments and rollbacks, an Evaluation module supporting LLM-as-a-judge and heuristic scoring, Experiments, a Playground, Human Annotation queues, Metrics dashboards with alerts, a native Model Context Protocol (MCP) server, a Public REST API, and a Query SDK.

Langfuse serves enterprise engineering teams building production AI agents and LLM applications (19 of Fortune 50, 2,300+ customers, 100,000+ engineers) as well as data-sensitive organizations self-hosting behind their firewall, and mid-market teams adopting through its open-source distribution. The company monetizes through a freemium SaaS cloud product (Free tier of 50k observations/month, usage-based Pro, quote-based Enterprise), a self-hosted Enterprise Edition sold under license, and, following its January 2026 acquisition by ClickHouse, co-distribution through ClickHouse's Cloud regions and enterprise sales channels. The MIT-licensed codebase, 29.6k GitHub stars, 300+ contributors, 100+ native integrations across model providers and agent frameworks, and compliance posture (SOC 2 Type II, ISO 27001, GDPR, HIPAA eligible) form the core of its product-led, community-led, and enterprise sales motions.

Short descriptiontext

Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, and metrics for production LLM and AI agent applications, used by 19 of Fortune 50 and 2,300+ customers.

Operating statusenum
Acquired
Ownership categoryenum
Headcount rangeband
11–50
akta.pro rankint
HeadquartersBerlin, Germany
HQ citystring
Berlin
HQ countrystring
Germany
HQ regionstring
Europe
Markets served

Serves global market

Offices2 records

Each record includes

City, Country, Type, Description, Source

Keyword5 values
LLM observability platform, AI agent tracing, prompt management software, LLM evaluation tools, AI engineering platform
Industry2 codes
1LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG)
CodeHDAEANADPrimaryYes
2Prompt Engineering, Orchestration & LLMOps Tooling
CodeHDAAACADPrimaryNo
NAICS code2 codes
  • Software Publishers5132
  • Software Publishers513210
SIC code1 code
  • Services-Prepackaged Software7372
Product category
LLM Observability Software
GTM motion4 records

Each record includes

Type, Description, Source

Revenue model4 records
1Langfuse Cloud (SaaS)
TypeSubscription Recurring
Description

Hosted cloud product sold as a tiered SaaS subscription. Free tier of 50k observations/month with no credit card required, plus paid Pro and Enterprise tiers. Customers can choose between EU, US, Japan, and HIPAA-eligible US data regions.

langfuse.com
2Usage-based cloud billing
TypeUsage Based
Description

Cloud usage is metered by observations (billable units), allowing land-and-expand as customer trace volume grows. The free tier caps at 50k observations/month, with Pro and higher tiers scaling by consumption.

langfuse.com
3Self-Hosted Enterprise Edition (license)
TypeLicensing Royalties
Description

On-premises/sovereign deployment requires an Enterprise Edition license key; advanced administrative features such as Data Retention are gated to the Enterprise Edition for self-hosted customers.

langfuse.com
4Freemium open-source distribution
TypeFreemium
Description

MIT-licensed open-source product with free self-hosting option acts as a funnel into paid Cloud and Enterprise Edition; the entire codebase, including all product features, is MIT-licensed and self-hostable for free.

langfuse.com
Marketing channels7 records

Each record includes

Title, Type, Stage, Description, Source

Distribution channels4 records

Each record includes

Title, Type, Scope, Target buyer, Description, Source

Cost components5 values
Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations
Pricing details4 tiers
1Free tier — 50k observations/month, no credit card required
ModelFreemiumBilling cadenceMonthly
Notes

50,000 observations/month free. Self-hosting is free under MIT license. Public demo project available.

langfuse.com
2Pro tier (Cloud)
ModelUsage-basedBilling cadenceMonthly
Notes

Usage-based billing on observations; specific dollar price points not publicly disclosed on the homepage. Available with EU, US, Japan, or HIPAA US data regions.

langfuse.com
3Enterprise tier (Cloud)
ModelSubscriptionBilling cadenceAnnual
Notes

Quote-based via "Talk to Sales" / "Get Demo"; includes enterprise-grade security and support.

langfuse.com
4Self-Hosted Enterprise Edition
ModelOne time/ perpetual licenseBilling cadenceMulti-year contract
Notes

Requires a license key for the Enterprise Edition; advanced administrative features such as Data Retention are gated to this edition for self-hosted customers.

langfuse.com
GTM typeB2B
B2B
Offering typeSoftware
Software
Core offering1 text field

Langfuse is an open source AI engineering platform that provides tracing, evaluation, prompt management, and metrics for LLM applications and AI agents. It captures hierarchical traces of every LLM call, tool invocation, and retrieval step, and offers self-hostable deployment under the MIT license alongside a managed Cloud SaaS and a Self-Hosted Enterprise Edition.

Differentiator
Functional benefit
Problem solved
Quantifiable outcome1 of 4 values shown
  • 50M+ SDK installs per month, indicating broad developer adoption.
+3 more records
Product and service10 records
1LLM Observability
CategoryCore platform module
Description

Hierarchical tracing module for capturing every LLM call, tool invocation, and retrieval step across AI agent and LLM applications; supports sessions, environments, sampling, masking, and multi-modality for engineering and MLOps teams.

2Prompt Management
CategoryCore platform module
Description

Version-control, deploy, and rollback prompts independently from application code with variables, message placeholders, prompt composability, folders, labels, caching, A/B testing, GitHub integration, and webhooks.

3Evaluation
CategoryCore platform module
Description

Run LLM-as-a-judge, heuristic code-based, and human review evaluators against production data or experiments with NUMERIC, CATEGORICAL, BOOLEAN, and TEXT score types.

4Metrics
CategoryCore platform module
Description

Dashboards and automated alerts tracking cost, latency, token usage, and quality with a Metrics API and Custom Dashboards over the ClickHouse OLAP store.

5Playground
CategoryCore platform module
Description

In-product testing surface that runs prompts from Prompt Management against real production inputs and compares multiple models side-by-side.

6Experiments
CategoryCore platform module
Description

Define dataset test cases and run experiments, comparing results side-by-side to evaluate application changes; integrates with Prompt Management and Evaluation modules.

7Human Annotation
CategoryCore platform module
Description

Collaborative human-in-the-loop workflows for reviewing traces and creating golden datasets via annotation queues.

8Langfuse MCP Server
CategoryAPI product
Description

Native Model Context Protocol server at /api/public/mcp with read and write tools, allowing AI assistants and agents to interact with Langfuse data programmatically across EU, US, Japan, HIPAA, and self-hosted deployments.

9Langfuse Cloud
CategoryCloud SaaS
Description

Hosted SaaS offering of the Langfuse platform with regional data residency in EU, US, Japan, and HIPAA-eligible US regions; tiered subscription with a free tier (50k observations/month), Pro, and Enterprise plans.

10Self-Hosted Enterprise Edition
CategorySelf-Hosted Enterprise Software
Description

On-premises/sovereign deployment of Langfuse requiring an Enterprise Edition license key; advanced administrative features such as Data Retention are gated to this edition for self-hosted customers.

Scale indicator13 records

Each record includes

Type, Value, Description, Source

Partnership12 partners
Strategic tierStrategic Ecosystem Partner (Via Clickhouse)TypeTechnology or IntegrationAnnounced on2026-05-01
Description

ClickHouse is deepening its ecosystem partnership with Confluent to support enterprise deployments; Langfuse benefits as part of the unified ClickHouse data platform for AI workloads.

Strategic tierFlagship — Acquirer And Primary Infrastructure PartnerTypeStrategic or Co-development PartnerAnnounced on2026-01-01
Description

ClickHouse acquired Langfuse GmbH in January 2026 concurrent with its $400M Series D funding round. The entire Langfuse team joined ClickHouse while maintaining Langfuse's open-source model, self-hosting options, and existing product contracts. Langfuse's LLM monitoring tool integrates with ClickHouse's database to track model latency and infrastructure usage; the companies plan to deepen the Langfuse–ClickHouse integration.

Strategic tierStrategic Cloud Deployment PartnerTypeTechnology or Integration
Description

Langfuse provides observability, tracing, and evaluation for enterprise AI applications and multi-agent systems deployed on OCI using either VM or Kubernetes (OKE) patterns. Supports native OCI Object Storage integration via LANGFUSE_USE_OCI_NATIVE_OBJECT_STORAGE.

Strategic tierMajor Hyperscaler IntegrationTypeTechnology or Integration
Description

Amazon Bedrock AgentCore has integrated Langfuse observability for detailed monitoring and debugging of AI agent performance. The implementation involves deploying Strands agents on Amazon Bedrock and configuring Langfuse for telemetry data to optimize costs and performance.

Strategic tierMajor Model Provider IntegrationTypeTechnology or Integration
Description

Native model provider integration in Langfuse, including Anthropic SDK, Claude Agent SDK (Python and JS), and Claude Code tracing/dev-tool integration. Anthropic's Model Context Protocol is also natively supported.

Strategic tierMajor Model Provider IntegrationTypeTechnology or Integration
Description

Native OpenAI integration including the Langfuse-wrapped OpenAI client, OpenAI Agents SDK integration, and the OpenAI o3/o4-mini/o3-pro cost tracking updates.

Strategic tierMajor Agent Framework IntegrationTypeTechnology or Integration
Description

Native LangChain integration with a CallbackHandler for Python and JavaScript, plus LangChain DeepAgents integration and interoperability between Langfuse and LangChain traces.

Strategic tierNo-Code Integration PartnerTypeTechnology or Integration
Description

Dify ships built-in Langfuse observability and analytics; users can connect Dify applications to Langfuse for tracing and evaluation.

Strategic tierMajor Cloud + Framework IntegrationTypeTechnology or Integration
Description

Native integrations with Google Gemini, Google Vertex AI, and Google ADK (Agent Development Kit) for tracing, evaluation, and prompt management.

Strategic tierStrategic Framework IntegrationTypeTechnology or Integration
Description

Native integration with the Vercel AI SDK for tracing, evaluation, and prompt management in Next.js / Vercel deployments.

Strategic tierEvaluation Integration PartnerTypeTechnology or Integration
Description

UpTrain.ai integration adds 20+ evaluators to Langfuse for LLM output evaluation.

Strategic tierMajor Cloud Deployment PartnerTypeTechnology or Integration
Description

AWS Marketplace and first-party deployment guide for self-hosting Langfuse on AWS using Terraform, with native integration of AWS S3, KMS encryption, and ElastiCache Redis.

Recent move6 records

Each record includes

Date, Type, Title, Description, Source

Expansion highlight6 records

Each record includes

Type, Description

Peers10 records
TypeDirect peer
Description

Closest direct competitor in LLM observability and evaluation. Arize Phoenix offers tracing, evaluation, and experiment tooling built on OpenTelemetry, targeting the same enterprise engineering teams that Langfuse serves, with overlapping integrations (OpenAI, Anthropic, LangChain, LlamaIndex).

TypeDirect peer
Description

Direct competitor focused on LLM evaluation, experimentation, and observability. Braintrust's loop of prompts, evals, and production traces is highly comparable to Langfuse's core product, and Braintrust is routinely named alongside Langfuse in industry buyer guides.

TypeDirect peer
Description

LangChain's first-party observability and evaluation product for LLM apps. Competes head-to-head with Langfuse on tracing and evals, with the strategic advantage of being bundled into the largest agent framework (LangChain/LangGraph).

TypeDirect peer
Description

Open-source LLM observability proxy that provides tracing, cost monitoring, and caching for LLM calls. Targets the same developer-led adoption motion and is frequently compared directly with Langfuse in production LLM monitoring benchmarks.

TypeDirect peer
Description

Specializes in LLM evaluation, simulation, and observability for production AI agents. Overlaps with Langfuse on eval workflows and agent tracing, and is regularly listed alongside Langfuse in 2025 LLM observability buyer guides.

TypeBroad incumbent
Description

Established observability platform for high-cardinality, production tracing. While not LLM-native, Honeycomb's OTel-based tracing and event analytics are increasingly used for LLM application observability, making it a broad incumbent Langfuse is positioned against at the enterprise level.

TypeBroad incumbent
Description

Public, large-scale APM and observability incumbent with a dedicated LLM Observability / Watchdog for AI Agents product. Represents the largest competitive threat from a broad incumbent, leveraging a deep enterprise install base and a unified APM/Logs/Security platform.

TypeBroad incumbent
Description

Long-standing APM and observability platform that has added AI/LLM monitoring capabilities. Competes with Langfuse indirectly at large enterprises that already standardize on New Relic for full-stack observability.

TypeBroad incumbent
Description

Enterprise observability and AIOps incumbent with a unified data platform. While primarily an infrastructure and APM vendor, Dynatrace's analytics platform is increasingly used for AI workload observability and is a competitor in enterprise procurement bake-offs.

TypeEmerging player
Description

AI observability and data-monitoring platform with LLM evaluation, drift detection, and guardrails. Has partial overlap with Langfuse on quality monitoring and serves a similar ML/AI engineering buyer, with a comparable emphasis on data-centric AI reliability.

Market position
Strengths5 records

Each record includes

Headline, Details, Source

Weaknesses5 records

Each record includes

Headline, Details, Source

Competitive moat6 records

Each record includes

Type, Details

Key risks6 records

Each record includes

Headline, Details, Source

Key highlights7 records

Each record includes

Headline, Details, Source

Customer concentration

Classification, Details

Named customers12 records

Each record includes

Name, Industry, Type, Use case, Source, UUID

Segment3 records

Each record includes

Title, Type, Primary, Description, Pain point addressed, Use case, Source

Ideal customer profile3 records

Each record includes

Profile, Firmographic size, Sales motion, Sales cycle length, Buying structure, Purchase trigger, Buyer persona, Geography, Industry vertical, Primary use case, Description, Pain points, Evidence proof points, Target buyer

Technology focused
Yes
API detail
Has APIbool
Yes

Docs URL, Description

Integration54 records

Each record includes

Title, Type, Description, Source

AI capability14 records

Each record includes

Type, Description, Source

AI maturity
App detail

Has app

Feature10 records

Each record includes

Title, Differentiator, Description, Source

Core technology
Revenue estimate
Valuation estimate
Number of profiles
Profiles3 records

Each record includes

Name, Designation, Designation category, Overview, Profile commentary, Source

No data
Compliance5 records

Each record includes

Name, Class, Description

Funding overview

Funding stage, Last funding date, Total funding USD

Funding rounds1 record

Each record includes

Round, Amount USD, Date, Pre money valuation, Total investors, Investors, News

Investors5 records

Each record includes

Name, Type, Date of entry, Rounds participated, Website

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Each record includes

Name, Acquisition type, Announced date, Completed date, Status, Website, News

Investment

Each record includes

Name, Round, Announced date, Lead investor, Website, News

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Langfuse

LLM Observability Softwarelangfuse.com

Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, and metrics for production LLM and AI agent applications, used by 19 of Fortune 50 and 2,300+ customers.

What Langfuse does

Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, metrics, and human annotation for production LLM and AI agent applications. The platform captures hierarchical traces of every LLM call, tool invocation, and retrieval step via OpenTelemetry-native instrumentation and stores them on a ClickHouse OLAP backend with PostgreSQL for transactional state, Redis/Valkey for async ingestion, and S3-compatible blob storage for large multi-modal payloads, enabling millisecond analytics across millions of traces at a reported 10B+ observations per month. Its product surface includes an LLM Observability module, version-controlled Prompt Management with one-click deployments and rollbacks, an Evaluation module supporting LLM-as-a-judge and heuristic scoring, Experiments, a Playground, Human Annotation queues, Metrics dashboards with alerts, a native Model Context Protocol (MCP) server, a Public REST API, and a Query SDK.

Langfuse serves enterprise engineering teams building production AI agents and LLM applications (19 of Fortune 50, 2,300+ customers, 100,000+ engineers) as well as data-sensitive organizations self-hosting behind their firewall, and mid-market teams adopting through its open-source distribution. The company monetizes through a freemium SaaS cloud product (Free tier of 50k observations/month, usage-based Pro, quote-based Enterprise), a self-hosted Enterprise Edition sold under license, and, following its January 2026 acquisition by ClickHouse, co-distribution through ClickHouse's Cloud regions and enterprise sales channels. The MIT-licensed codebase, 29.6k GitHub stars, 300+ contributors, 100+ native integrations across model providers and agent frameworks, and compliance posture (SOC 2 Type II, ISO 27001, GDPR, HIPAA eligible) form the core of its product-led, community-led, and enterprise sales motions.

Langfuse firmographics

Firmographics
Name
Langfuse
Legal name
Langfuse GmbH
Website
https://langfuse.com
Company type
Private
Founded year
2022
Operating status
Acquired
Headcount range
11–50 employees
Short description
Langfuse is an open-source AI engineering platform that provides observability, prompt management, evaluation, and metrics for production LLM and AI agent applications, used by 19 of Fortune 50 and 2,300+ customers.
Ownership category
akta.pro rank

Langfuse industry classification

Industry
Product category
LLM Observability Software
NAICS
Software Publishers (5132), Software Publishers (513210)
SIC
Services-Prepackaged Software (7372)
akta.pro primary industry
LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG) (HDAEANAD)
akta.pro secondary industry
Prompt Engineering, Orchestration & LLMOps Tooling (HDAAACAD)

Keywords

  • LLM observability platform
  • AI agent tracing
  • Prompt management software
  • LLM evaluation tools
  • AI engineering platform

Where Langfuse is headquartered

Location

Headquarters

HQ city
Berlin
HQ country
Germany
HQ region
Europe

Offices2 records

Markets served

Langfuse business model

Business model
GTM type
B2B
Offering type
Software
Cost components
Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations

Revenue model

  1. Langfuse Cloud (SaaS): Hosted cloud product sold as a tiered SaaS subscription. Free tier of 50k observations/month with no credit card required, plus paid Pro and Enterprise tiers. Customers can choose between EU, US, Japan, and HIPAA-eligible US data regions.
  2. Usage-based cloud billing: Cloud usage is metered by observations (billable units), allowing land-and-expand as customer trace volume grows. The free tier caps at 50k observations/month, with Pro and higher tiers scaling by consumption.
  3. Self-Hosted Enterprise Edition (license): On-premises/sovereign deployment requires an Enterprise Edition license key; advanced administrative features such as Data Retention are gated to the Enterprise Edition for self-hosted customers.
  4. Freemium open-source distribution: MIT-licensed open-source product with free self-hosting option acts as a funnel into paid Cloud and Enterprise Edition; the entire codebase, including all product features, is MIT-licensed and self-hostable for free.

Pricing tiers

ModelBillingPrice
FreemiumMonthlyFree tier — 50k observations/month, no credit card required
Usage-basedMonthlyPro tier (Cloud)
SubscriptionAnnualEnterprise tier (Cloud)
One time/ perpetual licenseMulti-year contractSelf-Hosted Enterprise Edition

Go-to-market motion4 records

Distribution channels4 records

Marketing channels7 records

Langfuse product offering

Product offering

Core offering

Langfuse is an open source AI engineering platform that provides tracing, evaluation, prompt management, and metrics for LLM applications and AI agents. It captures hierarchical traces of every LLM call, tool invocation, and retrieval step, and offers self-hostable deployment under the MIT license alongside a managed Cloud SaaS and a Self-Hosted Enterprise Edition.

Differentiator

Problem solved

Functional benefit

Products and services

  • LLM Observability Hierarchical tracing module for capturing every LLM call, tool invocation, and retrieval step across AI agent and LLM applications; supports sessions, environments, sampling, masking, and multi-modality for engineering and MLOps teams.
  • Prompt Management Version-control, deploy, and rollback prompts independently from application code with variables, message placeholders, prompt composability, folders, labels, caching, A/B testing, GitHub integration, and webhooks.
  • Evaluation Run LLM-as-a-judge, heuristic code-based, and human review evaluators against production data or experiments with NUMERIC, CATEGORICAL, BOOLEAN, and TEXT score types.
  • Metrics Dashboards and automated alerts tracking cost, latency, token usage, and quality with a Metrics API and Custom Dashboards over the ClickHouse OLAP store.
  • Playground In-product testing surface that runs prompts from Prompt Management against real production inputs and compares multiple models side-by-side.
  • Experiments Define dataset test cases and run experiments, comparing results side-by-side to evaluate application changes; integrates with Prompt Management and Evaluation modules.
  • Human Annotation Collaborative human-in-the-loop workflows for reviewing traces and creating golden datasets via annotation queues.
  • Langfuse MCP Server Native Model Context Protocol server at /api/public/mcp with read and write tools, allowing AI assistants and agents to interact with Langfuse data programmatically across EU, US, Japan, HIPAA, and self-hosted deployments.
  • Langfuse Cloud Hosted SaaS offering of the Langfuse platform with regional data residency in EU, US, Japan, and HIPAA-eligible US regions; tiered subscription with a free tier (50k observations/month), Pro, and Enterprise plans.
  • Self-Hosted Enterprise Edition On-premises/sovereign deployment of Langfuse requiring an Enterprise Edition license key; advanced administrative features such as Data Retention are gated to this edition for self-hosted customers.

Quantifiable outcome

  • 50M+ SDK installs per month, indicating broad developer adoption.
  • +3 more outcomes

Companies that use Langfuse

Customer profile

Named customers12 records

Segments3 records

Ideal customer profiles3 records

Langfuse technology and API

Technology

Technology focussed Yes

API detail

Has API
Yes
API docs
API detail

Core technology

AI maturity

App detail

Integration54 records

AI capability14 records

Feature10 records

Langfuse partnerships and signals

Strategic signal

Partnerships

Twelve partnerships are on record, tiered strategic ecosystem partner (via clickhouse), flagship — acquirer and primary infrastructure partner, strategic cloud deployment partner, major hyperscaler integration, major model provider integration, major agent framework integration, no-code integration partner, major cloud + framework integration, strategic framework integration, evaluation integration partner and major cloud deployment partner.

  • Confluentstrategic ecosystem partner (via clickhouse)Technology or Integration · 1 May 2026ClickHouse is deepening its ecosystem partnership with Confluent to support enterprise deployments; Langfuse benefits as part of the unified ClickHouse data platform for AI workloads.
  • ClickHouseflagship — acquirer and primary infrastructure partnerStrategic or Co-development Partner · 1 January 2026ClickHouse acquired Langfuse GmbH in January 2026 concurrent with its $400M Series D funding round. The entire Langfuse team joined ClickHouse while maintaining Langfuse's open-source model, self-hosting options, and existing product contracts. Langfuse's LLM monitoring tool integrates with ClickHouse's database to track model latency and infrastructure usage; the companies plan to deepen the Langfuse–ClickHouse integration.
  • Oracle Cloud Infrastructure (OCI)strategic cloud deployment partnerTechnology or IntegrationLangfuse provides observability, tracing, and evaluation for enterprise AI applications and multi-agent systems deployed on OCI using either VM or Kubernetes (OKE) patterns. Supports native OCI Object Storage integration via LANGFUSE_USE_OCI_NATIVE_OBJECT_STORAGE.
  • Amazon Bedrock (AgentCore)major hyperscaler integrationTechnology or IntegrationAmazon Bedrock AgentCore has integrated Langfuse observability for detailed monitoring and debugging of AI agent performance. The implementation involves deploying Strands agents on Amazon Bedrock and configuring Langfuse for telemetry data to optimize costs and performance.
  • Anthropicmajor model provider integrationTechnology or IntegrationNative model provider integration in Langfuse, including Anthropic SDK, Claude Agent SDK (Python and JS), and Claude Code tracing/dev-tool integration. Anthropic's Model Context Protocol is also natively supported.
  • OpenAImajor model provider integrationTechnology or IntegrationNative OpenAI integration including the Langfuse-wrapped OpenAI client, OpenAI Agents SDK integration, and the OpenAI o3/o4-mini/o3-pro cost tracking updates.
  • LangChainmajor agent framework integrationTechnology or IntegrationNative LangChain integration with a CallbackHandler for Python and JavaScript, plus LangChain DeepAgents integration and interoperability between Langfuse and LangChain traces.
  • Difyno-code integration partnerTechnology or IntegrationDify ships built-in Langfuse observability and analytics; users can connect Dify applications to Langfuse for tracing and evaluation.
  • Google (Vertex AI, Gemini, ADK)major cloud + framework integrationTechnology or IntegrationNative integrations with Google Gemini, Google Vertex AI, and Google ADK (Agent Development Kit) for tracing, evaluation, and prompt management.
  • Vercel (AI SDK)strategic framework integrationTechnology or IntegrationNative integration with the Vercel AI SDK for tracing, evaluation, and prompt management in Next.js / Vercel deployments.
  • UpTrain.aievaluation integration partnerTechnology or IntegrationUpTrain.ai integration adds 20+ evaluators to Langfuse for LLM output evaluation.
  • Amazon Web Services (AWS)major cloud deployment partnerTechnology or IntegrationAWS Marketplace and first-party deployment guide for self-hosting Langfuse on AWS using Terraform, with native integration of AWS S3, KMS encryption, and ElastiCache Redis.

Scale indicators13 records

Recent moves6 records

Expansion highlights6 records

Langfuse competitors and assessment

Company assessment

Direct peers

  • Arize AI (Phoenix): Closest direct competitor in LLM observability and evaluation. Arize Phoenix offers tracing, evaluation, and experiment tooling built on OpenTelemetry, targeting the same enterprise engineering teams that Langfuse serves, with overlapping integrations (OpenAI, Anthropic, LangChain, LlamaIndex).
  • Braintrust: Direct competitor focused on LLM evaluation, experimentation, and observability. Braintrust's loop of prompts, evals, and production traces is highly comparable to Langfuse's core product, and Braintrust is routinely named alongside Langfuse in industry buyer guides.
  • LangSmith (LangChain): LangChain's first-party observability and evaluation product for LLM apps. Competes head-to-head with Langfuse on tracing and evals, with the strategic advantage of being bundled into the largest agent framework (LangChain/LangGraph).
  • Helicone: Open-source LLM observability proxy that provides tracing, cost monitoring, and caching for LLM calls. Targets the same developer-led adoption motion and is frequently compared directly with Langfuse in production LLM monitoring benchmarks.
  • Maxim AI: Specializes in LLM evaluation, simulation, and observability for production AI agents. Overlaps with Langfuse on eval workflows and agent tracing, and is regularly listed alongside Langfuse in 2025 LLM observability buyer guides.

Broad incumbents

  • Honeycomb.io: Established observability platform for high-cardinality, production tracing. While not LLM-native, Honeycomb's OTel-based tracing and event analytics are increasingly used for LLM application observability, making it a broad incumbent Langfuse is positioned against at the enterprise level.
  • Datadog: Public, large-scale APM and observability incumbent with a dedicated LLM Observability / Watchdog for AI Agents product. Represents the largest competitive threat from a broad incumbent, leveraging a deep enterprise install base and a unified APM/Logs/Security platform.
  • New Relic: Long-standing APM and observability platform that has added AI/LLM monitoring capabilities. Competes with Langfuse indirectly at large enterprises that already standardize on New Relic for full-stack observability.
  • Dynatrace: Enterprise observability and AIOps incumbent with a unified data platform. While primarily an infrastructure and APM vendor, Dynatrace's analytics platform is increasingly used for AI workload observability and is a competitor in enterprise procurement bake-offs.

Emerging players

  • WhyLabs: AI observability and data-monitoring platform with LLM evaluation, drift detection, and guardrails. Has partial overlap with Langfuse on quality monitoring and serves a similar ML/AI engineering buyer, with a comparable emphasis on data-centric AI reliability.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

Langfuse social profiles

Digital presence

Langfuse compliance and trust

Trust signal

Compliance5 records

Langfuse financial estimates

Financial estimate

Revenue estimate

Valuation estimate

Langfuse leadership team

Management profile

Number of profiles

Profiles3 records

Langfuse funding detail

Funding detail

Funding overview

Funding rounds1 record

Investors5 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

Langfuse M&A and investment

M&A and investment

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Langfuse

What does Langfuse do?

Langfuse is an open source AI engineering platform that provides tracing, evaluation, prompt management, and metrics for LLM applications and AI agents. It captures hierarchical traces of every LLM call, tool invocation, and retrieval step, and offers self-hostable deployment under the MIT license alongside a managed Cloud SaaS and a Self-Hosted Enterprise Edition.

Is Langfuse a public or private company?

Langfuse is a private company. It is classified as corporate owned and is currently acquired.

When was Langfuse founded?

Langfuse was founded in 2022. It employs 11 to 50 people.

Where is Langfuse based?

Langfuse is headquartered in Berlin, Germany, in the Europe region.

How does Langfuse make money?

Four revenue lines are on record. Langfuse Cloud (SaaS) is the primary driver. The others are usage-based cloud billing, self-Hosted Enterprise Edition (license) and freemium open-source distribution.

Who are Langfuse's main competitors?

Direct peers on record are Arize AI (Phoenix), Braintrust, LangSmith (LangChain), Helicone and Maxim AI. Broad incumbents are Honeycomb.io, Datadog, New Relic and Dynatrace. WhyLabs is listed as an emerging player.

Does Langfuse have an API?

Yes. Langfuse exposes a REST-based Public API at /api/public (Basic Auth with project-scoped public/secret keys), a query SDK for programmatic data access, blob storage export to S3/GCS/Azure, and a native Model Context Protocol (MCP) server at /api/public/mcp (streamableHttp transport) with both read and write tools. The MCP server is scoped per-project via API key authentication, is offered across Cloud EU, Cloud US, Cloud Japan, HIPAA US, and self-hosted deployments, and supports client setup via Claude Code, Cursor, and other MCP clients. Endpoints are versioned (legacy /api/public and v3 endpoints such as /api/public/v3/scores). Developer documentation is at langfuse.com/docs/api-and-data-platform/overview.

What industry is Langfuse in?

Langfuse's product category is LLM Observability Software. Its primary akta.pro industry code is HDAEANAD, LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG), with a secondary code of HDAAACAD, Prompt Engineering, Orchestration & LLMOps Tooling. Its NAICS code is 5132 and its SIC code is 7372.

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HackerNoonTwo Acquisitions Deep, Two Still Standing: What's Really Happening to Open-Source LLM ObservabilityAn analysis of four open-source LLM observability tools — Langfuse, Helicone, Opik and Phoenix — found that Langfuse was acquired by ClickHouse on January 16, 2026, and Helicone by Mintlify on March 3, 2026. ClickHouse said Langfuse remains 100% open-source and self-hostable, while Mintlify put Helicone in maintenance mode with no open-source commitment. Opik and Phoenix are still independently run.TalkMarketsOpen Source LLM Observability: A Smarter Way to Monitor AI ApplicationsThe article introduces Spanlens as an open-source LLM observability platform designed to help development teams monitor AI applications by tracking metrics such as token consumption, costs, latency, and agent workflows. It positions the tool as a flexible, self-hosted alternative to existing solutions like Langfuse, Helicone, Braintrust, and LangSmith, emphasizing its proxy-first integration and OpenTelemetry support.Open Source For YouFrom Black Box To Glass Box: Observability Strategies For Production AIThe article outlines strategies for implementing open-source observability tools to monitor and govern production AI systems, addressing the unique challenges of non-deterministic outputs and invisible quality degradation in LLM pipelines. It highlights a reference architecture utilizing OpenTelemetry, Grafana, LangFuse, and other specialized tools to provide vendor-neutral visibility into token costs, latency, and model performance. The piece argues that building this infrastructure is essential for enterprises to ensure reliability, control costs, and meet regulatory requirements as they scale AI adoption.MarkTechPostTop LLM Observability and Evaluation Platforms in 2026: Langfuse, LangSmith, Braintrust, Arize, and More ComparedThis article compares eight leading LLM observability and evaluation platforms in 2026 across three axes: tracing depth, evaluation capability, and production monitoring. The platforms reviewed are Langfuse, LangSmith, Braintrust, Arize AI, MLflow, Weights & Biases Weave, Helicone, and Datadog LLM Observability, organized into four market camps: AI-native observability platforms, open-source evaluation libraries, AI gateways, and APM extensions. Market data cited projects the LLM observability platform market to grow from $2.69 billion in 2026 to $9.26 billion by 2030 at a 36.2% CAGR, with OpenTelemetry GenAI semantic conventions emerging as the industry standard for vendor-neutral instrumentation.PitchBookThe boom in AI cost-cutting startups may just be a token gestureStartups offering AI cost-management tools are proliferating as enterprises seek to cut runaway AI spending, but investors and founders are skeptical this represents a durable standalone venture opportunity, with one suggesting there may not be a $10 billion company in the space. Major funding rounds continue to be raised—Fireworks AI closed a $1.5 billion Series D at a $17.5 billion valuation and Braintrust raised an $80 million Series B—while consolidation is also occurring, including Stripe's reported $1 billion acquisition of Metronome and ClickHouse's acquisition of Langfuse. Historical precedent from cloud and data-warehouse cost optimization startups that failed to achieve breakout success in the last decade underpins investor caution about the longevity of pure-play AI cost-optimization businesses.StartupHub.aiLangfuse: Domain Expertise Crucial for AI Self-Impr…The article discusses Langfuse's approach to AI self-improvement, presenting Annabelle Sch\u00e4fer's argument that domain expertise and high-signal feedback (clear yes/no target functions) are essential for building effective improvement loops for AI agents. Langfuse conducted an experiment on arXiv paper classification that demonstrated a 15 percentage point accuracy improvement from 68% to 83% using clear target functions with a simple GPT-5-4-nano model. The article outlines a three-step methodology for building self-improvement systems: working with domain experts, reviewing production data, and designing systems that generalize.CRNThe 10 Coolest AI Observability And Governance Tools Of 2026 (So Far)AI observability has emerged as a critical challenge for organizations deploying AI systems at scale, creating demand for tools to monitor AI performance, detect hallucinations, track data access, and manage token costs. The article profiles 10 AI observability and governance tools available in 2026 from both startups and established technology providers, highlighting platforms from LogicMonitor and others. Notable M&A activity in this space includes ClickHouse's acquisition of Langfuse in January and Cisco Systems' purchase of Galileo Technologies in April to enhance their respective observability offerings.Confident-Ai11 Best AI Evaluation Tools for Testing & Improving AI Applications in 2026A comprehensive guide ranking and comparing 11 AI evaluation tools for 2026 has been published, covering platforms, open-source frameworks, and hybrid solutions evaluated across six dimensions including metric depth, use case coverage, collaboration accessibility, production integration, CI/CD automation, and pricing transparency. The guide is produced by Confident AI, which is positioned as the top recommendation for cross-functional teams needing comprehensive evaluation coverage across agents, chatbots, RAG, and safety use cases. Tools analyzed include Arize AI, LangSmith, DeepEval, LangWatch, Langfuse, Braintrust, Ragas, Galileo AI, Weights & Biases, and Deepchecks.Confident-AiTop 7 AI Agent Observability Platforms for 2026This article is a 2026 product comparison guide ranking the top 7 AI agent observability platforms, written and published by Confident AI as the primary subject and apparent author. The guide evaluates each platform across dimensions including trace visibility, evaluation capabilities, pricing, and target use cases, with Confident AI positioned as the top overall recommendation due to its evaluation-first approach and closed-loop quality workflow. Additional platforms covered include Langfuse, Arize/Phoenix, LangWatch, LangSmith, Braintrust, and Helicone, each serving different segments from open-source tracing to cost analytics.PydanticBest AI observability platform in 2026This article is a 2026 comparison guide for AI observability platforms, explaining how they solve problems traditional monitoring cannot—including silent quality failures, invisible agent behavior, runaway costs, and root causes outside the model. The guide evaluates six major platforms: Pydantic Logfire (recommended as best overall for production AI applications with full-stack tracing and transparent pricing), Langfuse (best open-source self-hosted option), LangSmith (best for LangChain/LangGraph stacks), Arize AI (best for evaluation-heavy ML teams), Braintrust (best for eval-driven CI/CD workflows), and Datadog LLM Observability (best for existing Datadog customers). The article includes pricing comparisons, feature analyses, and recommendations for teams choosing based on their stack, data-residency requirements, or existing vendor relationships.