Building Production RAG: How Hierarchical Chunking Solves Hallucinations

Most RAG failures stem from naive document chunking that fragments context, causing LLMs to hallucinate or return irrelevant answers. The vector database and embeddings are not the problem—it's the chunks themselves that lack awareness of their surrounding context. Combining hierarchical chunking with hybrid search (vector + keyword matching) is essential for reliable, production-grade RAG systems.