OpenLIT is an open-source, self-hosted tool for developing AI apps. It allows for LLM experimentation, prompt management, secure API key handling, and protection against prompt injection. It also offers OpenTelemetry-native observability for the GenAI stack.
Hello PH!!! I'm Aman, the maintainer of OpenLIT, and I'm thrilled to announce our second launch—OpenLIT 2.0! 🚀
With this version, we're enhancing our open-source, self-hosted AI Engineering and analytics platform to make it even more powerful and effortless to integrate. We understand the challenges of evolving an LLM MVP into a robust product—high inference costs, debugging hurdles, security issues, and performance tuning can be hard AF. OpenLIT is designed to provide essential insights and ease this journey for all of us developers.
Here's what's new in OpenLIT 2.0:
- ⚡ OpenTelemetry-native Tracing and Metrics
- 🔌 Vendor-neutral SDK for flexible data routing
- 🔍 Enhanced Visual Analytical and Debugging Tools
- 💭 Streamlined Prompt Management and Versioning
- 👨👩👧👦 Comprehensive User Interaction Tracking
- 🕹️ Interactive Model Playground
- 🧪 LLM Response Quality Evaluations
As always, OpenLIT remains fully open-source (Apache 2) and self-hosted, ensuring your data stays private and secure in your environment while seamlessly integrating with over 30 GenAI tools in just one line of code.
Check out our Quickstart Guide (https://docs.openlit.io/latest/q...) to see how OpenLIT 2.0 can streamline your AI development process.
If you're on board with our mission and vision, we'd love your support with a ⭐ star on GitHub (https://github.com/openlit/openlit).
I'm here to chat and eager to hear your thoughts on how we can continue improving OpenLIT for you! 😊
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About OpenLIT 2.0 on Product Hunt
“Open source dashboard for AI engineering & LLM data”
OpenLIT 2.0 launched on Product Hunt on January 16th, 2025 and earned 141 upvotes and 1 comments, placing #10 on the daily leaderboard. OpenLIT is an open-source, self-hosted tool for developing AI apps. It allows for LLM experimentation, prompt management, secure API key handling, and protection against prompt injection. It also offers OpenTelemetry-native observability for the GenAI stack.
OpenLIT 2.0 was featured in Open Source (68.3k followers), Developer Tools (511.1k followers) and Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 163.6k products, making this a competitive space to launch in.
Who hunted OpenLIT 2.0?
OpenLIT 2.0 was hunted by Aman Agarwal. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how OpenLIT 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Aman Agarwal