Create, curate, and prepare data by performing transformations without IT intervention.
Easily review data prior to model ingestion.
Build and edit supervised and unsupervised modes using an easy low code interface.
Access latest neural network and gradient-boosted trees libraries.
Real automation integrates seamlessly into current systems so that data follows a clear data lineage and controlled end-to-end path.
Track all events, logs, training, predictions, and explainer runs.
Reference documented model training statistics and SHAP-based explainers.