Glossary

Memory Compression refers to the systematic process by which an agentic AI system condenses, abstracts, and restructures large volumes of historical data, interactions, and experiences into compact, high-value representations that can be efficiently stored, retrieved, and reasoned over.

A Memory Retrieval Strategy in agentic AI refers to the systematic approach an autonomous agent uses to identify, select, and retrieve relevant information from its memory systems—such as short-term, long-term, episodic, semantic, or procedural memory—at the right time and in the right form to support reasoning, planning, and decision-making.

MLOps, short for Machine Learning Operations, refers to streamlining the deployment, monitoring, management, and governance of machine learning (ML) models in production.