Vector database
Definition
A vector database stores text, images or records as numeric embeddings and finds the entries closest in meaning to a query. It is the search layer behind retrieval-augmented generation, enabling semantic lookups where keyword search fails.
Instead of matching words, it matches meaning: a query about "payment reminder" also finds documents that say "overdue notice".
In operational systems it sits alongside the relational database, not instead of it. Facts, amounts and states stay in the transactional system; the vector index only helps find the right context.
In practice
- Semantic search across contracts, manuals, tickets and e-mail
- Must carry access metadata so results respect permissions
- Complements, never replaces, the system of record
Related terms
- Retrieval-augmented generation (RAG)Retrieval-augmented generation is a method in which relevant company documents are searched first and the retrieved passages are given to the language model as context. The model answers from those passages, which makes answers current, source-linked and auditable.
- Large language model (LLM)A large language model is a statistical model trained on very large text corpora that predicts likely continuations of text. It can classify, summarise, translate and draft, and it is the reasoning component inside most AI agents — but it holds no live company data by itself.
- API integrationAn API integration connects two systems through their programming interfaces so data moves automatically and reliably. It is the stable alternative to manual re-entry, CSV exchange and interface robots, and it is the backbone of every serious automation.