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AI Memory

Definition

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

Memory helps agents preserve continuity. It can include user preferences, prior actions, account history, business rules, project state, conversation summaries, and workflow progress.

For SMBs, memory is what makes an agent feel less like a vending machine and more like an operating teammate. But memory must be governed carefully. The business needs to know what is stored, where it is stored, who can access it, and when it should be forgotten.

Related terms

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.

Model Context Protocol

Model Context Protocol, often called MCP, is an emerging standard for connecting AI systems to tools, data sources, and external context.

Retrieval-Augmented Generation

Retrieval-augmented generation, or RAG, is a method where an AI system retrieves relevant information before generating an answer or taking action.

Vector Databases

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