Decoder. plain-English AI glossary

Model Registry

▲ Rising

Central repository that tracks model versions, metadata, and lineage—who trained it, what data, which metrics.

Think of it like

A library card catalog that lists every books author, edition, and condition.

Example

MLflow Model Registry storing model artifacts, stage (dev/prod), and approval history so teams share the source of truth.

How it actually works

Solves model sprawl—teams lose track of which version is in production and why. Enables rollbacks, A/B testing, and compliance audits. Integration with CI/CD and serving systems ensures consistency. Can be as simple as S3 with metadata or as elaborate as MLflow/DVC.

For product teams

Reduces deployment incidents and accelerates time to production by removing ambiguity.

For engineers

API to register, retrieve, and tag model artifacts; integrates with serving systems to pull correct version at runtime.

Checkpoint — Stores.
Versioning — Enables.

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