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WeKnora: turn scattered documents into one queryable knowledge system

WeKnora: turn scattered documents into one queryable knowledge system

WeKnora Most teams do not have a knowledge problem. They have a scattered documents problem, and every answer starts with another search. WeKnora, from Tencent, turns raw documents into one system you can query three ways: fast RAG answers with citations, a multi-step agent that can use tools and skills, and a wiki that organises the same knowledge into linked pages. A new upload merges into existing pages, and deleting a document rewrites or removes the pages that cited it. Version 0.9.0 arrived on 29 October 2026 with an in-app assistant, multi-agent collaboration, and automations. It now has 36,779 stars on GitHub and runs self-hosted with Docker, or as a single Lite binary. What you get Three ways to query the same knowledge: cited RAG answers, a tool-using agent, and a linked wiki Knowledge that stays consistent: uploads merge into existing pages, deletions rewrite or remove the pages that cited them Self-hosted with Docker, or as a single Lite binary Version 0.9.0 adds an in-app assistant, multi-agent collaboration, and automations Start with the documents your team already searches for, and let the wiki grow from what people actually ask. Repo: https://github.com/Tencent/WeKnora Quick poll What would you use WeKnora for first? Fast RAG answers with citations The multi-step agent The auto-built wiki Self-hosting it with Docker Vote in the comments. If you found WeKnora interesting, I write about tools like this every week in The AI-Native Engineering Leader, what actually works for engineering leaders building with AI agents, and what to skip.

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