What’s New:
ModelOp Center v2.5 contains a powerful set of new features to increase AI governance and visibility, as well as streamline further model risk processes.
Orchestrate:
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MLC
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Creation UX Enhancements: intuitive, drop-down for
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adding ModelOp Center-specific processing into model life
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cycle (
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•MLC Simplification: simplified standard MLCs (e.g. Promotion mlc’s) by replacing sub-processes with delegates
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MLC) designs, as well as additional simplified out-of-the-box MLC templates
Custom Metadata from Ticketing Systems: ability to pull in
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custom metadata from Jira and ServiceNow tickets to be persisted with the Model metadata in ModelOp Center
Runtime Selection: more flexible runtime
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•SageMaker MLC view optimization: ability to hide SageMaker MLC’s that are not fired during snapshot
•UI DMN Editor: built-in DMN editor
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selection and associated orchestration
Monitor & Visualize•
Microsoft PowerBI Integration: integration with Microsoft PowerBI
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to power custom dashboarding using ModelOp Center data
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Business Value Tracking (beta): example Business Value Tracking monitors with integration into Tableau Dashboards for executive reporting
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UI Editor for Monitoring thresholds: built-in editor for defining monitoring thresholds, allowing for users to enter simple metric checks or complex, rules-driven thresholds based on monitoring metrics and model metadata.
OOTB Monitoring improvements: minor improvements to OOTB monitors for error handling & versioning
Govern:•
Automated Model Documentation: ability to auto-generate documentation with model-specific metadata, tests, and other information, using a base document template
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Model Risk Process Automation: powerful model life cycle automations to orchestrate the key steps in the model risk and compliance processes
General:•
UI – Runtimes
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Enhancements: simplified and intuitive UI for
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viewing the current status and troubleshooting model execution environments (runtimes)
Performance Improvements:
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substantial performance improvements across the ModelOp Center UI
Python 3.8 Support in Runtime: standard, supported Python 3.8 base images for the ModelOp Runtime
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Iterative dev/test
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: ability for customers to test models in the ModelOp Runtime before official registration and management
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Runtime Logs Viewing:
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enhanced live view into runtime logs for
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troubleshooting