Experiments
Experiments allow ML engineers and data scientists to track training runs, log hyperparameters and metrics, and compare results across iterations.
Models
The Model Registry is where trained models are registered, versioned, and promoted through lifecycle stages — from development to staging to production.
Auto ML
Auto ML automates model selection and training. Users provide a dataset and a target, and the platform runs the selection and evaluation process automatically, surfacing the best-performing model with metrics for review.
AI Gateway
AI Gateway lets teams deploy trained models as REST API endpoints. It supports both models hosted inside the tenant cluster and external model providers.