Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data. By integrating seamlessly into existing workflows, Langfuse streamlines the process of monitoring, debugging, and optimizing LLM applications. Our platform's robust documentation and active community support make it easy for developers to leverage Langfuse for enhancing their LLM projects efficiently. Whether you're troubleshooting interactions or iterating on new features, Langfuse is committed to simplifying your LLM development journey.
Companies of all sizes are investing in building new tools or improving their current toolstack with the use of AI. They want to be in control, avoid sensitive data leakages, misuse of the tool or brand reputational damage. Langwatch analyzes your AI solutions, evaluates the quality, prevents AI risks, and helps you improve and ship with confidence.
Based on our record, Langfuse should be more popular than LangWatch. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Langfuse is another open-source platform for debugging, analyzing, and iterating on language model applications. It offers tracing, evaluation, and prompt management. While Langfuse offers many capabilities, some (like the Prompt Playground and automated evaluation) are only available in the paid tier for self-hosted users. - Source: dev.to / 7 days ago
It is reportedly used on websites like Langfuse and Million.dev. - Source: dev.to / about 2 months ago
LangFuse is a monitoring and debugging platform for LLM-powered applications. It provides insights into token usage and costs. It can also analyze latency, and the performance of AI interactions. The platform allows debug prompts, and analyzes how they behave in production. - Source: dev.to / 3 months ago
You'll notice there's a lot of prompts in these examples. As you develop your prompts, you'll likely want to iterate and refine them over time. I recommend using tools like Langfuse or Langsmith for prompt management and metrics, making it easier to track performance and make improvements. - Source: dev.to / 3 months ago
Langfuse (https://langfuse.com). We started with observability and have branched out into more workflows over time (evals, prompt mgmt, playground, testing...). We have a bunch of traction and are looking for our fourth to sixth hire in scaling and building feature depth. We're hiring in person (4-5 days/week) in Berlin, Germany (salary ranges for each job 70k-130k, up to 0.35% equity). We value quality in... - Source: Hacker News / 3 months ago
When I started LangWatch, I had a crystal clear development vision for it in mind, I had been through it all, from starting my first business and entangling myself in code so messy I couldn’t move any longer (and therefore losing money and sleep), to working on a consultancy with perfect TDD, pairing and couldn’t-be-more-refactored codebase (sleeping, oh, so well!), to incredibly messy code again this time done by... - Source: dev.to / 4 months ago
LangSmith - Build and deploy LLM applications with confidence
AssemblyAI - Robust and Accurate Multilingual Speech Recognition
Datumo Eval - Discover Datumo Eval, the cutting-edge LLM evaluation platform from Datumo, designed to optimize AI model accuracy, reliability, and performance through advanced evaluation methodologies.
Athina AI - Athina helps developers to build reliable LLM applications.
Braintrust - Braintrust connects companies with top technical talent to complete strategic projects and drive innovation. Our AI Recruiter can 100x your recruiting power.
LLM Prompt & Model Playground - Test LLM prompts & models side-by-side against many inputs