ModelOp Center

The agnostic enterprise ModelOps platform

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Gartner Report: Market Guide for AI Trust, Risk and Security Management
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Masterclass Series: Managing AI/ML Model Risk
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2021 ModelOps Summit:
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The agnostic enterprise ModelOps platform

Govern and Scale Enterprise AI Initiatives
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

Forrester

Through 2023, at least 50% of IT leaders will struggle to move their AI predictive projects from proof of concept to production maturity
Gartner Keynote Presentation from ModelOps Summit:
The AI Engineering Journey
Regulators and lawmakers across the globe — including the U.S. and EU — are issuing guidance and announcing upcoming laws that intend to regulate the use of AI for fairness and transparency. The EU proposes to issue steep fines, up to 6% of annual revenue, to companies who do not comply.

Gartner

Market Guide for AI Trust, Risk and Security Management 

September 2021, Avivah Litan, Farhan Choudhary, Jeremy D’Hoinne
Answer Your Board’s AI questions with ModelOps
See the Value You Get With ModelOp Center
Organizations increase revenue benefits of AI initiatives by up to 30% with ModelOp Center
Organizations increase revenue benefits of AI initiatives by up to 30% with ModelOp Center
Calculate the potential value you can recognize with ModelOp Center
What People Are Saying About ModelOp Center
Dan Moore, COO QBE North America
What people are saying about ModelOp Center
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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.
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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.
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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 and manage them overtime.
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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.
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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.
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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 and Finally, we have a single pane of glass on the entire enterprise models in production, with a 24x7 control over their life cycles.
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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.
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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.
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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.
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Govern and Scale Your Enterprise AI Initiatives
Real-time Monitoring
Immediately detect and remediate model performance issues
Continuous Compliance
Establish and enforce business and technical controls with a rules-based engine
Automated Model Life Cycles
Orchestrate the steps in entire model life cycle with integration to DevOps, IT and business systems and applications

Getting Started With ModelOp Center Is Easy