The Verta Model Catalog is a place to find, publish, and use ML models (or model pipeline components.) Similar to container registries like DockerHub or Python package registries like PyPi, builders of models and ML pipelines can publish ready-to-consume components to the Verta Model Catalog.
Where does a Model Catalog fit into the ML Lifecycle?
Model Catalog is like a staging area between experimentation and production where model developers go from hundreds of experiments (in an experiment management system) to just a handful that make it to production. The Model Catalog allows your organization to have an accurate view of all models in the development lifecycle and in production and to consolidate key information about those registered models.
What are the benefits of a model catalog?
With model documentation and versioning, it enables easy handoff to consumers of your models.
It provides a central place to impose governance and controls on your models.
It allows you to automate your release processes by integrating with CI/CD tools like Jenkins.