Why Most RAG Systems Fail in Production: The Hidden Architecture Problems Behind AI Search

Building a reliable RAG system is not about connecting an LLM to a vector database. It requires a complete architecture covering data ingestion, retrieval, ranking, evaluation, and production operations.

This article is the first part of a five-part series where we will explore how modern RAG systems are designed, why naive implementations fail, and what it takes to build AI search systems that work reliably in production.

Production RAG Architecture Series

Why Most RAG Systems Fail in Production: The Hidden Architecture Problems Behind AI Search (you are here)

Building a Production RAG Pipeline: Document Processing, Chunking, and Metadata Design