AI Metadata Store

Log, Search and Compare metadata from experiments, models and checkpoints. Support for logging metrics and events from various services involved in training and deployment of models.

Model Registry

Track and store trained models or upload them to a built in artifact server. Automatically apply recipes to transform models to representations understood by inference platforms and runtimes.

Continuous Model Evaluation

Measure performance metrics such as throughput and accuracy of models. Write deployment checks based on metrics to automatically tag models to promote to production.