Evaluate & optimize your LLM performance with DSPy
LangWatch is the ultimate platform for LLM performance monitoring and optimization. Streamline pipelines, analyze metrics, evaluate prompts, and ensure quality. Powered by DSPy, we help AI developers ship 10x faster with confidence. Create an account for free.
Hello Product Hunters!! 🚀
I’m Manouk, co-founder of LangWatch. You may haven't heard from us in a while, but trust me—you’ll love this new ProductHunt launch. We’ve been listening and have solved your biggest pain points in building LLM applications. 🥁 And the best part? We have opened-up the access to all users.
We’re thrilled to be live on Product Hunt today with our biggest release yet: LangWatch Optimization Studio!
After building our powerful Monitoring & Evaluation platform, there was still a major pain point you shared with us. So, we solved it:
This new feature takes LLM development to the next level, solving the most frustrating challenges teams face when optimizing LLM pipelines and ensuring top-tier performance.
With the newest Optimization Studio, you can:
⚡ Evaluate & Optimize: Experiment different prompts and LLM-models automatically in seconds (with DSPy)
🧠 Custom Evaluations: Build tailored evaluations and bring them back to your real-time monitoring.
🔄 Seamless Deployment: Confidently push optimized prompts/few-shot examples and pipelines into production.
A few highlights of LangWatch:
🌟 Observability: Monitor LLM performance, latency, costs, and quality.
📊 User-Analytics: Deeply understand what docs of your RAG are mostly used and topics discussed.
👩💻 Evaluations: Run evaluations to control for hallucinations or other criteria you care about real-time.
✏️ Prompt Management: Version, tweak, and deploy prompts directly from LangWatch.
🔬 Datasets: Build datasets of non-performing traces and start improving.
🐒 API: All analytics and features available per API.
🌍 Open Source: Join our growing community on GitHub to collaborate and contribute.
Get started today:
⭐ GitHub: https://github.com/langwatch/lan...
📖 Docs: https://docs.langwatch.ai/
⏯️ Live Training Today: https://lu.ma/um4owj65
If you're already a fan of DSPy, we'd love to hear about what you've built and explore how we can support you even more!
A big thanks to the PH community for all your feedback and support. We’re here all day and can’t wait to hear your thoughts, questions, and feedback!
Cheers,
Manouk
