
Langfuse is the ๐บ๐ผ๐๐ ๐ฝ๐ผ๐ฝ๐๐น๐ฎ๐ฟ ๐ผ๐ฝ๐ฒ๐ป ๐๐ผ๐๐ฟ๐ฐ๐ฒ ๐๐๐ ๐ข๐ฝ๐ ๐ฝ๐น๐ฎ๐๐ณ๐ผ๐ฟ๐บ. It helps teams collaboratively develop, monitor, evaluate, and debug AI applications. Langfuse can be ๐๐ฒ๐น๐ณ-๐ต๐ผ๐๐๐ฒ๐ฑ in minutes and is battle-tested and used in production by thousands of users from YC startups to large companies like Khan Academy or Twilio. Langfuse builds on a proven track record of reliability and performance. Developers can trace any Large Language model or framework using our SDKs for Python and JS/TS, our open API or our native integrations (OpenAI, Langchain, Llama-Index, Vercel AI SDK). Beyond tracing, developers use ๐๐ฎ๐ป๐ด๐ณ๐๐๐ฒ ๐ฃ๐ฟ๐ผ๐บ๐ฝ๐ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐, ๐ถ๐๐ ๐ผ๐ฝ๐ฒ๐ป ๐๐ฃ๐๐, ๐ฎ๐ป๐ฑ ๐๐ฒ๐๐๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐ฒ๐๐ฎ๐น๐๐ฎ๐๐ถ๐ผ๐ป ๐ฝ๐ถ๐ฝ๐ฒ๐น๐ถ๐ป๐ฒ๐ to improve the quality of their applications. Product managers can ๐ฎ๐ป๐ฎ๐น๐๐๐ฒ, ๐ฒ๐๐ฎ๐น๐๐ฎ๐๐ฒ, ๐ฎ๐ป๐ฑ ๐ฑ๐ฒ๐ฏ๐๐ด ๐๐ ๐ฝ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ by accessing detailed metrics on costs, latencies, and user feedback in the Langfuse Dashboard. They can bring ๐ต๐๐บ๐ฎ๐ป๐ ๐ถ๐ป ๐๐ต๐ฒ ๐น๐ผ๐ผ๐ฝ by setting up annotation workflows for human labelers to score their application. Langfuse can also be used to ๐บ๐ผ๐ป๐ถ๐๐ผ๐ฟ ๐๐ฒ๐ฐ๐๐ฟ๐ถ๐๐ ๐ฟ๐ถ๐๐ธ๐ through security framework and evaluation pipelines. Langfuse enables ๐ป๐ผ๐ป-๐๐ฒ๐ฐ๐ต๐ป๐ถ๐ฐ๐ฎ๐น ๐๐ฒ๐ฎ๐บ ๐บ๐ฒ๐บ๐ฏ๐ฒ๐ฟ๐ to iterate on prompts and model configurations directly within the Langfuse UI or use the Langfuse Playground for fast prompt testing. Langfuse is ๐ผ๐ฝ๐ฒ๐ป ๐๐ผ๐๐ฟ๐ฐ๐ฒ and we are proud to have a fantastic community on Github and Discord that provides help and feedback. Do get in touch with us!
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