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Learn About MLOps
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Learn About ModelOps
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Learn About ModelOps

ModelOps: Govern and Scale
Enterprise AI Initiatives

Explore the Platform
AI Portfolio Management
AI Governance
AI Operational Assurance
Know the ROI of your AI initiatives.
AI Portfolio Management shows you the performance, contribution and compliance of every model across your enterprise.
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Ensure continuous compliance.
AI Governance makes it fast and easy to define and establish business, risk, and compliance rules for the entire model life cycle.
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Faster, more reliable, and less costly AI.
AI Operational Assurance standardizes and automates model operations 24×7 for the Heterogenous Enterprise.
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ModelOp Center AI Portfolio Management Dashboard
AI Operational Assurance Dashboard
Pillars of ModelOp
AI Portfolio Management
Know the ROI of your AI initiatives. AI Portfolio Management shows you the performance, contribution and compliance of every model across your enterprise.
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AI Governance
Ensure continuous compliance. AI Governance makes it fast and easy to define and establish business, risk, and compliance rules for the entire model life cycle.
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AI Operational Assurance
Faster, more reliable, and less costly AI. AI Change Management 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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Case Study: AI Model Operations at Scale (Fidelity)
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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
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
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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
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Why ModelOps

Answer Your Board’s AI Questions with ModelOps

Getting Started With ModelOp Center Is Easy

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WHAT PEOPLE ARE SAYING ABOUT MODELOP CENTER
“
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."
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Govern and Scale Enterprise AI Initiatives
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Gartner Disclaimer
Any reference made to “ModelOps” is about model operations platforms, not the company ModelOp. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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