V3.0 Release Notes

Owned by Dave Trier
Nov 10, 2022
2 min read

What’s New:

ModelOp Center v3.0 contains a powerful set of new features to increase AI governance and visibility, as well as streamline further model risk processes.

Orchestrate:

  • Model Risk & Compliance MLC’s: out of the box templates for orchestrating the typical steps required for model risk management

  • Conditional MLC Start: support for triggering MLC with specific conditions, allowing for specific MLC’s to be initiated in a more streamlined and manageable approach

  • MLC Incident Management: integrated tracking of MLC-specific technical incidents, including troubleshooting the incident and resuming the process instance

 

Monitor & Visualize

  • Comprehensive UX Refresh: updated UI, including a revamped home page dashboard, updated visualizations, a new compliance module, and additional operational reporting/notifications

  • Executive Dashboard: executive-level dashboard that contains business, operations, risk, and data science KPI’s

  • Operations Dashboard: operations-specific dashboards that contain an overview of all deployments and issues across all environments

  • Integrated Business Value: out-of-the-box templates to track business value for models. Automated detection of deviations from expected business value thresholds, with automated notifications and roll-up reporting

 

Govern:

  • Model Audit Reporting: new Reporting module that allows users to generate detailed risk/audit reports for all models used for production decisioning

  • Risk & Compliance Dashboards: executive-level dashboards that contain an overview of current status of models from a compliance/risk perspective

  • Automated Model Risk Processes: ability to configure documentation and processes that are enforced across a variety of different use cases/business units to ensure adherence to overall AI governance procedures and processes.

 

General:

  • Azure AKS: support for running ModelOp Center on Azure AKS

  • Azure Blob Storage: support for leveraging Azure Blob Storage for model artifacts as well as for model-specific training/test/etc. data

  • Python 3.9 Support in Runtime: standard, supported Python 3.9 base images for the ModelOp Runtime

 

Specific Details:

 

Minor Enhancements:

 

 

Bug Fixes:

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