An AI Model Registry is a centralized system for organizing and tracking machine learning models throughout their development and production lifecycle. It records model versions, associated metadata, evaluation results, deployment status, and other information needed to identify which model is being tested, approved, or actively serving predictions.
A model registry provides controlled transitions between stages such as development, validation, staging, and production. It helps teams compare model versions, maintain an auditable history of changes, roll back problematic releases, and coordinate model deployment across environments. It is an important component of MLOps and enterprise AI operations.
