Deployment

Model Registry

Definition

A centralised repository for versioning, cataloguing, and managing trained ML models throughout their lifecycle—from experimentation through staging to production. A model registry is the foundation of reproducible, auditable AI deployments.

Related Terms

MLOps

The practice of combining Machine Learning, DevOps, and data engineering to streamline the deployment, monitoring, and maintenance of ML models in production. MLOps ensures reliable, scalable, and reproducible ML systems across their entire lifecycle.

Model Serving

The process of deploying trained ML models to production environments where they can receive inputs and return predictions at scale. Model serving infrastructure must address throughput, latency, versioning, and cost while meeting SLAs.

Model Card

A short document accompanying a trained AI model that describes its intended uses, performance across demographic groups, limitations, and ethical considerations. Model cards promote transparency and are considered best practice under frameworks like the EU AI Act and ISO 42001.

Related Services

Product Leadership Program

Eu Ai Act Compliance

Knowing the Terms Is Step One. Applying Them Is Step Two.

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