Dense retrieval is a method of information retrieval that uses neural network-generated embeddings to find semantically relevant content — as opposed to spar…
Technical implementation · AI Search Infrastructure
Dense retrieval is a method of information retrieval that uses neural network-generated embeddings to find semantically relevant content — as opposed to sparse retrieval, which matches based on keyword frequency. Dense retrieval systems compare vector representations of queries and documents to identify meaning-based matches.
Dense retrieval is the engine behind modern AI search. When Perplexity or Google AI Overviews retrieve content to ground their answers, they are using dense retrieval systems — not keyword search. Content that is semantically rich, covers a topic’s full conceptual territory, and uses the language of the domain performs better in dense retrieval than content optimized for keyword repetition.