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I built a self-hosted RAG system that actually works — here's how to run it in one command
How-ToMachine Learning

I built a self-hosted RAG system that actually works — here's how to run it in one command

via Dev.toFrancesco Marchetti2h ago

I'll be honest: I spent weeks trying to make existing RAG tools work for my use case. AnythingLLM kept needing cloud APIs. RAGFlow was hard to self-host cleanly. Perplexity-style tools were completely off the table for anything with sensitive documents. So I built my own. RAG Enterprise is a 100% local RAG system — no data leaves your server, no external APIs, no hidden telemetry. It runs on your hardware with a single setup script. Here's how to get it running. Why another RAG tool? Because my clients have real constraints: Legal documents that can't touch US servers (hello, GDPR) IT departments that won't approve "just use OpenAI" Budgets that don't include $500/month SaaS subscriptions I needed something that runs on-prem, handles PDFs and DOCX files well, supports multiple users with proper roles, and doesn't require a PhD to install. After building and iterating on this for a few months, it now handles 10,000+ documents comfortably, supports 29 languages, and the whole stack is co

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