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Langfuse

https://langfuse.com Research Team Data
Active

Open-source LLM engineering platform for tracing, observability, prompt management, evals, experiments and human annotation.

Langfuse brings LLM observability, prompt management, evaluations, experiments and human annotation into a connected workflow. It is open source, self-hostable and designed to help teams debug, monitor and improve LLM applications and agents.

Positioning

Open-source LLM observability and evaluation platform

Key facts

HQ location
Berlin, Germany
Founded
2023
Employee range
11-50 (11-50)
Funding stage
Seed
Company type
Private (Private / open-source commercial)
Pricing model
Licensing Open Source Usage Based (Open-core with cloud plans, usage-based/seat-based and self-hosting options)
Last updated
Jun 21, 2026

Revenue estimate

Unknown / not publicly disclosed

Valuation estimate

Unknown

Investments

$4M seed (Lightspeed, YC, La Famiglia); funding not fully disclosed beyond seed

Target customers

AI engineers, developers and teams building LLM applications and agents

Key competitors

LangSmith, Helicone, PromptLayer, Arize AI, Braintrust, Galileo

Known customers

Unknown / not comprehensively disclosed

Classification (raw research text)

Core focus
LLM observability and evaluation
Core industry
Enterprise AI Development
Core category
LLM observability

Shown verbatim from the research spreadsheet — deriving structured segment/industry tags from this text is a future phase.

Attribute breakdown

  • AI Workflows Secondary feature
  • System / API Integration Secondary feature
  • Prompt Management / Prompt Engineering Primary focus
  • Retrieval-Augmented Generation Secondary feature
  • AI / LLM Data Pipeline Secondary feature
  • AI Quality Assurance / LLM Evaluation Primary focus
  • AI Observability / Monitoring Primary focus
  • Human-in-the-Loop Review / Feedback Primary focus
  • Analytics / BI / Decision Intelligence Secondary feature
Show all 32 attributes
  • AI Workflows Secondary feature
  • AI Automation / Business Process Automation Not emphasized
  • AI Fine-tuning / Custom Model Training Not emphasized
  • Agent Builder / Agent Configuration Not emphasized
  • Multi-agent Orchestration / Runtime Not emphasized
  • System / API Integration Secondary feature
  • Prompt Management / Prompt Engineering Primary focus
  • Retrieval-Augmented Generation Secondary feature
  • Graph RAG / Knowledge Graph Retrieval Not emphasized
  • Enterprise Search / Knowledge Management Not emphasized
  • AI / LLM Data Pipeline Secondary feature
  • Document AI / Document Processing Not emphasized
  • Model Deployment / Inference Infrastructure Not emphasized
  • Traditional Machine Learning Not emphasized
  • AI Quality Assurance / LLM Evaluation Primary focus
  • AI Observability / Monitoring Primary focus
  • AI Security / Guardrails Not emphasized
  • Data Privacy / PII / Confidential AI Not emphasized
  • AI Governance / Policy Management Not emphasized
  • AI Risk / Compliance Not emphasized
  • AI Asset Inventory / Model Registry Not emphasized
  • Human-in-the-Loop Review / Feedback Primary focus
  • Call Transcription / Speech-to-Text Data Capture Not emphasized
  • Conversation Intelligence / Speech Analytics Not emphasized
  • Text Chatbots / Conversational Assistants Not emphasized
  • Voice AI Agents Not emphasized
  • Voice Infrastructure / STT / TTS Not emphasized
  • AI for Customer Experience / Support Automation Not emphasized
  • Sales / Revenue Intelligence Not emphasized
  • Analytics / BI / Decision Intelligence Secondary feature
  • Enterprise App / Internal Tool Builder Not emphasized
  • Vertical-Specific AI Not emphasized