RAG Systems Fail Due To Data Issues

An explainer outlines why Retrieval-Augmented Generation (RAG) systems often underperform, identifying weaknesses across data collection, chunking, embeddings, retrieval strategy, prompt design, and monitoring. It highlights that poor preprocessing and embedding quality, incorrect chunking, and weak retrieval frequently lead to hallucinations and irrelevant answers, and recommends simple optimizations—data hygiene, better chunking, evaluation, and guardrails—to improve accuracy and maintainability.