ModelOps: Govern and Scale
Enterprise AI Initiatives

Executive Visibility for AI
Model Risk Industrialization
AI Orchestration
Know the ROI of your AI initiatives.
Executive Visibility for AI shows you the performance, contribution and compliance of every model across your enterprise.
Stop model validation backlog growth.
Model Risk Industrialization standardizes and automates model risk processes, accelerating model validation and compliance reporting.
Ensure Enterprise AI model Governance.
AI Orchestration standardizes and automates model operations 24×7 for the Heterogenous Enterprise.
Pillars of ModelOp
Executive Visibility for AI
Know the ROI of your AI initiatives. Executive Visibility for AI shows you the performance, contribution and compliance of every model across your enterprise.
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Model Risk Industrialization
Stop model validation backlog growth. Model Risk Industrialization standardizes and automates model risk processes, accelerating model validation and compliance reporting.
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AI Orchestration
Ensure critical models are always running within SLAs. AI Orchestration standardizes and automates model operations 24×7 for the Heterogenous Enterprise.
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Case Studies

ModelOp Success Stories

QBE uses AI to accelerate claims processing and improve customer experience
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Royal Bank of Canada Capital Markets optimizes bond trading with AI and ModelOp Center
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F500 Financial Services Company reduces fraud and bootstrap ModelOps Enterprise Solution
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BBSI achieves near real-time credit scoring updates with ModelOp
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LEADING ANALYSTS’ VIEWS ON MODELOPS
ModelOps lies at the center of any organizations’ enterprise AI strategy, it is an enabling technology that is key to converging various AI artifacts, platforms and solutions, while ensuring scalability and governance."
Gartner, ”Innovation Insight for ModelOps”
Farhan Choudhary, Shubhangi Vashisth, Arun Chandrasekaran, Eric Brethenoux, 6 August 2020
Your AI transformation is doomed without ModelOps."
Forrester, ”Introducing ModelOps to Operationalize AI”
Kjell Carlsson, Ph.d., and Mike Gualtieri, August 13, 2020
Why ModelOps

Answer Your Board’s AI Questions with ModelOps

Getting Started With ModelOp Center Is Easy

WHAT PEOPLE ARE SAYING ABOUT MODELOP CENTER
Productionizing AI initiatives with ModelOp Center has unlocked enormous potential and we are looking forward to diving into this discussion. Serving customers better, not just in claims, but at every point in their experience is always a priority at QBE."
Dan Moore, COO QBE North America
The unique business process approach of ModelOp Center not only solves the deployment, monitoring and governance of models, it also creates the bridge between different worlds: Operations, IT and Data Science."
As a Business Unit Leader, I was struggling to measure the ROI from AI projects. ModelOp Center is a true business accountable solution that provides us with the ability to add business KPIs and thresholds to each model and manage them over time."
Being a traditional bank with legacy systems, we needed a product that could keep us competitive with the fintech companies, and incorporating Machine Learning models into existing programs, and managing all the models we have would have not been possible without ModelOp Center."
The automation aspect of ModelOp Center is saving us resources and is giving us the peace of mind knowing that our AI programs are under control and any compliance issue can be addressed quickly."
Being able to define a Model Life Cycle for each model, with triggers, threshold and alerts is the best feature of ModelOp Center, as it saves us resources, and it prevents manual errors. Finally, we have a single pane of glass on the entire enterprise models in production, with a 24x7 control over their life cycles."
With ModelOp Center, the frustrating process of deploying and maintaining models is over. I can create any model with any language or platform, onboard it and make any changes over time."
In a fast-moving space such as AI, we wanted to avoid any lock-ins, ModelOp Center agnosticism is giving us this flexibility and we didn’t have to rip-and-replace our existing AI investments."
For DevOps people like myself, it was unconceivable the lack of consistency in deploying and managing Data Science products. ModelOp Center gave discipline to the operationalization of AI/ML models, similarly to what DevOps did for software."

What Is Your Organization's AI Maturity?