A cloud-agnostic platform that automates and manages the entire machine learning lifecycle, including experiment tracking, pipeline orchestration, and model deployment across hybrid and multi-cloud environments.

A system within the platform that automatically versions and stores all machine learning assets including code, datasets, models, metrics, and logs to maintain full experiment lineage and reproducibility.