Anthropic Contextual Retrieval: Prepend 50-100 Token Context to Each Chunk Before Embedding for 49-67% Fewer RAG Failures
Anthropic·high signal
Standard RAG splits documents into chunks that lose surrounding context—Anthropic's Contextual Retrieval prepends a 50-100 token LLM-generated explanation to each chunk before embedding and BM25 indexing. Combined Contextual Embeddings + Contextual BM25 reduces top-20 retrieval failure from 5.7% to 2.9% (49% drop); adding a reranker pushes it to 67%. The context generation step adds minor cost but is cacheable.