Introducing Contextual Retrieval

Contextual Retrieval is a method that significantly improves the retrieval step in Retrieval-Augmented Generation (RAG). It uses two sub-techniques, Contextual Embeddings and Contextual BM25. This method can reduce the number of failed retrievals by 49% and, when combined with reranking, by 67%. These represent significant improvements in retrieval accuracy, which directly translates to better performance in downstream tasks. Contextual Retrieval is uniquely possible at low cost with Claude, thanks to its special prompt caching feature.