Ask HN: Should I Combine Global Knowledge, Internet Search, and User RAG
I'm building a SaaS platform in Sri Lanka that handles documents and other sensitive data.Each user can upload their own documents and information, and the platform uses RAG to answer questions based on that user's data. That part makes sense to me.My main concern is what happens when the user hasn't uploaded enough information. However, I'm not sure if I'm thinking about this correctly.I'd really appreciate hearing how others would approach this problem
- ▪I'm building a SaaS platform in Sri Lanka that handles documents and other sensitive data.Each user can upload their own documents and information, and the platform uses RAG to answer questions based on that user's data.
- ▪That part makes sense to me.My main concern is what happens when the user hasn't uploaded enough information.
- ▪However, I'm not sure if I'm thinking about this correctly.I'd really appreciate hearing how others would approach this problem
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I'm building a SaaS platform in Sri Lanka that handles documents and other sensitive data.Each user can upload their own documents and information, and the platform uses RAG to answer questions based on that user's data. That part makes sense to me.My main concern is what happens when the user hasn't uploaded enough information. I still want the LLM to provide accurate answers using reliable information from the internet (or from a curated knowledge base), with proper citations.These are the two architectures I'm considering:Option 1:Base LLM (OpenAI/Anthropic via Azure AI Foundry or Amazon Bedrock) ↓ Platform RAG (global knowledge base managed by us) ↓ User-specific RAG In this approach, we maintain a global knowledge base that we (the platform admins) curate and update.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.