How to Build an AI-Powered Internal Knowledge Base
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our team built an internal kb powered by embeddings and rag. heres the architecture and lessons learned
also worth noting – the testing suggestions from AI tools are actually really good
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what chunking strategy did you land on? fixed size vs semantic chunking makes a huge difference for retrieval quality - we burned like 2 weeks figuring that out
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rag is solid but dont overlook access control on the retrieval layer. if different employees have different doc permissions, your kb can accidentally surface confidential stuff to the wrong people. seen it happen.
appreciate the detailed breakdown. copilot has genuinely made me like 30% faster at coding
just tried this and yeah it works. claude code is my go-to for complex refactoring tasks now