Blog

TL;DR RAG systems often fail not because of poor embeddings or weak LLMs, but because they feed irrelevant information to the generation stage. Initial retrieval casts a wide net, returning documents that are semantically similar but not actually relevant to […]

TL;DR Document chunking is the foundation of every RAG system, yet it’s often treated as an afterthought. The wrong chunking strategy can cripple your RAG performance regardless of how sophisticated your embedding model or LLM is. Poor chunking leads to […]