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70% of Enterprise RAG Deployments Fail Before Production. Here's What Kills Them.

DEV Community·Gabriel Anhaia·about 1 month ago
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#ai#rag#llm#database#chunk#query
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Book: RAG Pocket Guide Also by me: Database Playbook My project: Hermes IDE | GitHub — an IDE for developers who ship with Claude Code and other AI coding tools Me: xgabriel.com | GitHub The global RAG market is on track to clear $40 billion in 2026. According to vendor write-ups, somewhere between 70% and 80% of the enterprise RAG projects feeding that number never reach production ( Blits.ai, 2026 , Ragaboutit, 2026 ). The demos are great. The pilots ship a deck. Then someone tries to point the chatbot at the actual document corpus and the thing falls apart in a small, embarrassing way. Picture the kind of failure a team I talked to ran into. Their internal HR bot quoted an old parental-leave policy to an employee who was checking what they were entitled to. The current policy had been live on the intranet for months. The chatbot had never re-indexed it. The team that owned the bot did not know the bot had drifted, because nothing on the dashboard tracked source freshness against retrieval. The link works.…

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