Preprocessing that divides large source documents into meaningful pieces sized for retrieval and embedding in a RAG system. Explore its practical uses.
Chunking splits long documents into pieces, often several hundred tokens each, before they are embedded and retrieved by a RAG system. Chunk size and split boundaries directly affect retrieval quality. Cutting through sentences or paragraphs can remove context and cause retrieval of misleading fragments. A common approach respects semantic units such as paragraphs and includes some overlap between adjacent chunks. The best strategy varies for code, legal documents and transcripts, so practical implementations should compare alternatives experimentally.
A strategy for optimizing content so that brands and their content can be cited in the single answers generated by AI search systems or voice assistants.
Some websites are seeing sharp increases in site: operator queries in Search Console performance reports. Explore possible causes, measurement effects and diagnostic responses.
