---
title: How does Langfuse make money?
description: "How Langfuse makes money: a commercial open-source model with Langfuse Cloud as the managed service, alongside self-hosted Enterprise plans."
---

# How does Langfuse make money?

Langfuse is a commercial [open source](/handbook/chapters/open-source) company. We monetize by offering Langfuse Cloud as a fully managed service.

Langfuse OSS can be [freely self-hosted](/self-hosting) without scalability or performance limitations compared to Langfuse Cloud and we do not sell commercial support for it.

## How we think about pricing

- Langfuse prices should always be a no-brainer for customers to understand and agree with.
- We do not price based on number of seats as the problems we solve are inherently collaborative. pricing based on usage is more aligned with the value of Langfuse.
- All our products should be free to use for small scale or side projects; we do this through self-hosting and the Cloud Hobby plan.
- As Langfuse grows, we benefit from economies of scale on Langfuse Cloud; we are working hard to lower (instead of raising) prices wherever possible.
- We only want to monetize customers who get real value from Langfuse; if a customer is unhappy and not using us we are easy going about refunds.

## Value proposition of Langfuse Cloud

- Cost-effective compared to self-hosting due to shared infrastructure and overhead
- Infrastructure and [pricing](/pricing) that scales with your usage without needing to maintain or upgrade infrastructure
- Includes [support](/support) by the core team
- Always up-to-date with the latest features and bug fixes

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## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/handbook/chapters/monetization.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.