Langfuse

Langfuse develops an open-source observability and analytics platform for LLM (Large Language Model) applications, enabling developers to trace, debug, and understand the impact of changes on their LLM-powered applications. The platform supports tracing of LLM chains and measuring the quality of outputs, providing visibility into how models perform in production and how prompt changes, model swaps, or pipeline modifications affect application behavior. As an open-source solution, Langfuse differentiates itself by offering LLM observability that developers can self-host and customize, avoiding vendor lock-in while providing the tracing, evaluation, and analytics capabilities needed to build reliable LLM applications. The platform serves the growing ecosystem of developers building production applications on top of LLMs, where understanding model behavior, debugging failures, and maintaining quality across iterations are critical challenges. Langfuse addresses the observability gap that emerges when LLM applications move from prototypes to production, where traditional application monitoring tools lack the context to understand LLM-specific behaviors like prompt chains, token usage, latency patterns, and output quality metrics. Founded in 2022 and headquartered in Berlin, Germany, Langfuse has raised $4.5 million in a Seed round backed by Y Combinator, La Famiglia, and Lightspeed Venture Partners.

Serial Founder

College Wise > Nanyang Technological University (NTU), London School of Economics and Political Science, Technical University of Munich, WHU – Otto Beisheim School of Management, University of Oxford