AI Transformation with ModelOps

Want To Measure Your Enterprise AI Initiatives? Start With Model Debt

Stu Bailey, Forbes – June 30, 2020

There’s a growing awareness of the widening gap between the ability of data scientists to create models and the ability to deploy them in production. This has driven growing interest in ModelOps, which is the enterprise-wide discipline that enables organizations to scale and govern their AI initiatives by managing models and their life cycles from creation through retirement. But until now, there have been few objective metrics that organizations can use to gauge the effectiveness of their ModelOps programs, or indeed their AI initiatives. The concept of model debt helps to address that need.

Read the Full Article

All ModelOp Blog Posts 

ModelOp Announces ModelOp Center Release 2.2

ModelOp Announces ModelOp Center Release 2.2

New ModelOp Center Capabilities Improve Governance, Management and Monitoring of Artificial Intelligence and Machine Learning Models ModelOp Center unlocks the value of AI and ML investments, reducing model operationalization costs by as much as 30% and accelerating...

Are Your Model Governance Practices ‘AI Ready’?

Are Your Model Governance Practices ‘AI Ready’?

Stu Bailey, Forbes – November 18, 2020 For some industries, the use of AI and machine learning models is novel, but several industries—consumer finance and insurance in particular—have been building, using and governing models for decades. These industries have...

Critical Success Factors in Enterprise Model Governance

Critical Success Factors in Enterprise Model Governance

In consumer finance and insurance, businesses have been building, using, and governing models for decades. The adoption of unstructured data and advanced computational techniques is adding new layers of complexity that affect model deployment and the associated...

ModelOps Is Just The Beginning Of Enterprise AI

ModelOps Is Just The Beginning Of Enterprise AI

Jun Wu, Forbes – October 9, 2020 Most of this year, enterprises have been reviewing the lessons learned in the past few years from their Enterprise AI initiatives, i.e., what has worked, what hasn’t, and how to move forward to modernize their infrastructures and take...