Skip to content

Vector Databases

Definition

Vector databases store data as embeddings so AI systems can retrieve information based on semantic similarity rather than exact keyword matches.

Vector databases are commonly used in retrieval systems for AI agents. They allow an agent to find relevant documents, examples, policies, customer records, or knowledge snippets even when the user does not use the exact same wording.

For Growth Marshal's audience, the point is that agents need a way to find meaning, not just match words. If a customer asks, "Can I pause my plan?" the system should retrieve cancellation, billing, retention, and account policy context even if none of those exact terms appear in the prompt.

Related terms

AI Memory

AI memory is the ability of an AI system to retain useful context across interactions, tasks, users, or workflows.

Knowledge Graphs

Knowledge graphs are structured maps of entities, relationships, attributes, and facts that help systems understand how information connects.

Long-Term Memory for Agents

Long-term memory for agents refers to persistent memory that allows agents to retain information across sessions and over time.

Semantic Search

Semantic search retrieves information based on meaning and intent rather than exact keyword matching.