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Contextual retrieval: context-prefixed chunks + hybrid search + reranking
Before embedding/indexing a chunk for retrieval, prepend a short LLM-generated note situating it within the full document (e.g. 'this is from ACME's Q2 2023 SEC filing...'), then retrieve using both embeddings and BM25 keyword search together, optionally adding a reranking pass.
Why this verdict?
Anthropic reports this combination cutting top-20-chunk retrieval failure from 5.7% to 2.9% (49% fewer failures), and to 1.9% (67% fewer) with reranking added -- each layer contributes independently. It remains the reference approach for chunk-based RAG rather than having been superseded by something else.