Retrieval, Memory & Knowledge
Chunking
Splitting documents into smaller pieces for more effective retrieval and processing.
Definition
When indexing documents for RAG, large documents are typically split into smaller pieces called chunks — a paragraph, a page, or a fixed number of tokens. This is because retrieval works best when the returned content is focused and relevant. If you retrieve an entire 200-page document, most of it will be irrelevant noise. The chunking strategy — how to split documents and how large each chunk should be — significantly affects retrieval quality.
Related Terms
RAG (Retrieval-Augmented Generation)
Combining an LLM with a search system so it can look up current or specific information before responding.
Vector Database
A database that stores embeddings and allows searching by meaning rather than keywords.
Indexing
Organising content so it can be searched efficiently.
Heard enough terminology — ready to talk outcomes?
We translate AI concepts into measurable business results. No upfront fees — you pay only when independently verified results are delivered.
Disclaimer
This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.
Document reference: ISO_webpage_knowledge-base_glossary_v1
Last modified: 29 March 2026