What is Chunking?
Chunking is the process of splitting documents into passages small enough to retrieve precisely and large enough to stay meaningful. Chunk boundaries decide what an AI system can find, so poor chunking silently caps answer quality.
Also known as: document chunking, chunk size RAG.
Naive fixed-length splitting cuts tables in half and separates a heading from the rule it introduces. Structure-aware chunking follows the document's own layout - sections, clauses, table rows, slide frames - and keeps the parent context attached to each passage.
Chunk metadata matters as much as chunk text: document title, section path, page number, effective date and access level all travel with the passage and make citation and permission filtering possible.
How Uthereal handles it
Uthereal chunks by document structure and keeps page and section metadata, which is what makes page-accurate citations possible.
Related reading
Last updated 2026-09-18 · plain-text glossary for AI tools