Bring all your ML assets into a single catalog for clear visibility and easier governance across external devices
Maintain a central catalog of all models and all their associated versions, including metadata, versions and associated artifacts
Record which devices are running what version of a model
Track and manage different versions of models, enabling easy comparison and rollback
Standardize model documentation with an AI documentation copilot
Streamline deployment with standardized processes
Easily containerize models for consistent deployment across various environments
Deploy models to remote devices but coordinate centrally
Define standardized workflows for model deployment, versioning and retirement across edge devices, IoT devices, network endpoints and other remote locations
Easy model versioning of on-device models
Monitor and manage all your models consistently through a single platform
Configure governance checklists with process gates to ensure regulatory compliance and Responsible AI
Monitor performance across the full model portfolio, regardless of where deployed
Surface remote issues back to central command
Maintain audit logs to ensure compliance and traceability
