Why does Langfuse exist?

Accelerate the deployment of reliable, safe, and cost-effective AI applications and agents.

Today

AI will create meaningful value for society and drive economic growth. We are still in the early days of seeing this impact. Over time, every successful company will be an AI company, with AI at the core of its strategy, value creation, and business processes. Most value creation will happen at the application-layer, split between incumbents and AI-native startups.

Today, the primary blocker to more deployments is making applications reliable, safe, scalable, explainable, and affordable.

We’re building an integrated and open tooling layer that helps teams solve these issues faster:

• Visibility & explainability → Langfuse Observability (production tracing, metrics, and analytics)
• Collaboration across disciplines → Prompt management, shareable views & dashboards
• Evaluation & data operations → Langfuse Evaluations (evals, datasets, labeling)

We are independent, vendor-neutral, and available as cloud or self-hosted at production scale.

Where are we going?

The ecosystem evolves quickly: model capabilities improve, inference gets cheaper, and agents can work longer on harder problems. As this happens, the focus shifts from “How do we make it work?” to “How does it work, how do we improve it, and who is accountable?”

Our bet:

• Production tracing is the source of truth for AI applications and agents.
• Evals are a means to an end, closing the loop from experiment to production and back.
• Teams need a neutral observability and data layer to understand, govern, and continuously improve AI systems at scale, while the underlying models, frameworks and technologies evolve.