Definition · AI in finance
Vector database
Vector database is a store for embeddings that enables similarity search. For vector database, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
Also known as vector store, vector DB
Why it matters
Understanding vector database matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo uses a connected ontology and semantic model rather than a vector database, so relationships between systems are explicit and numbers trace to source records.
In practice
Governance example
Teams use vector database when they evaluate whether an AI-assisted analysis can be trusted. The useful test is whether the output is tied to approved data, repeatable logic, human review, and an audit trail.
Pluvo example
Pluvo uses a connected ontology and semantic model rather than a vector database, so relationships between systems are explicit and numbers trace to source records.
In practice, teams should define vector database with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding vector database matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo uses a connected ontology and semantic model rather than a vector database, so relationships between systems are explicit and numbers trace to source records.
A strong workflow for vector database separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Pluvo uses a connected ontology and semantic model rather than a vector database, so relationships between systems are explicit and numbers trace to source records.
FAQ
What is a vector database?
Vector database is a store for embeddings that enables similarity search. For vector database, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
How is a vector database different from a knowledge graph?
The boundary for vector database differs from related terms by scope, source data, time period, and decision use. In this glossary, it covers what a vector database is — a store for embeddings that enables similarity search — and how it underpins RAG retrieval, so teams should compare those boundaries before using it in reporting or planning.