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.
Based on our record, Langfuse should be more popular than Humanloop. 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.
Humanloop | London and San Francisco | Full time in person | https://humanloop.com Humanloop is building infrastructure for AI application development. We're the LLM Evals Platform for Enterprises. Duolingo, Gusto, and Vanta use Humanloop to evaluate, monitor, and improve their AI systems. ROLES:. - Source: Hacker News / 5 months ago
- https://humanloop.com/) for teaching me the philosophy of implementing a copilot textarea. I wish I could have used the project directly, but integrating just one React component into Rails while keeping importmap and StimulusJS was quite challenging. Given the limited time, I decided to move on with StimulusJS. This is our first time building an open-source project to share with the world, and we’re a bit... - Source: Hacker News / 9 months ago
- Conversational simulation is an emerging idea building on top of model-graded eval” - AI Startup Founder Things to consider when comparing options: “Types of metrics supported (only NLP metrics, model-graded evals, or both), level of customizability; supports component eval (i.e. Single prompts) or pipeline evals (i.e. Testing the entire pipeline, all the way from retrieval to post-processing)” “+method of... - Source: Hacker News / over 1 year ago
Humanloop (YC S20) | London (or remote) | https://humanloop.com We're looking for exceptional engineers that can work at varying levels of the stack (frontend, backend, infra), who are customer obsessed and thoughtful about product (we think you have to be -- our customers are "living in the future" and we're building what's needed). Our stack is primarily Typescript, Python, GPT-3. Please apply at... - Source: Hacker News / about 2 years ago
https://humanloop.com/ Find the prompts users love and fine-tune custom models for higher performance at lower cost. - Source: Hacker News / over 2 years ago
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 / 5 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 / 2 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
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