Build an AI community manager in seconds
EigentBot deploys an AI-powered community manager in seconds! - Seamlessly integrate with web links, files, Notion, GitHub, LinkedIn, and more. - Prioritizing privacy, we support local model deployment. - With one-click, get your bot running in just 3 seconds!
Hi 👋 everyone, We are the Eigent-AI / Camel-AI team, focused on building the open-source multi-agent framework. Many developers and AI startups in our open-source community are working on innovative AI-native products and running their communities on platforms like Discord. We’ve developed a lightweight Discord user service bot powered by agentic RAG technology to support these AI builders and open-source communities. Eigentbot allows users to upload personalized knowledge bases, including Webli
Congrats on launching Eigenbot! Been following Camel AI open source community since last year, what a great community!! Discord has been a big community for AI and crypto to manage their supporters. We at Opencord AI also use Discord as well! We will def try out this eigenbot to offload some of our tasks👏 thanks for launching it on PH!
Congrats on launching Eigentbot, Eigent-AI/Camel-AI team! 🎉 The ability to integrate personalized knowledge bases into a lightweight Discord user service bot is such a practical tool for open-source communities and AI-native startups. The one-click deployment feature is a game-changer, making it super easy for developers to get started, and local model deployment is perfect for those who need more control. Excited to see how Eigentbot empowers communities with features like agentic RAG technolog
Congrats on the launch! Would love to be able to try the bot out directly on the website as well. Maybe this would help people see the value faster! Keep shipping :D
Amazing. Congrats on the launch team, excited about this!
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.