What is ModelOps? And MLOps?
“ModelOps lies at the center of any organizations’ enterprise AI strategy”
“AI model operationalization (ModelOps) is primarily focused on the governance and life cycle management of all AI and decision models (including models based on machine learning, knowledge graphs, rules, optimization, linguistics and agents).
In contrast to MLOps, which focuses only on the operationalization of ML models, and AIOps which is AI for IT Operations, ModelOps focuses on the operationalization of all AI and decision models.”
Gartner, “Innovation Insight for ModelOps”, Farhan Choudhary, Shubhangi Vashisth, Arun Chandrasekaran, Erick Brethenoux, 6 August 2020
ModelOps is about creating a shared service that runs across the organization — enabling robust scaling, governance, integration, monitoring and management of various AI models. Adopting a ModelOps strategy should facilitate improvements to the performance, scalability and reliability of AI models. ModelOps aims to eliminate internal friction between teams by sharing accountability and responsibility. It protects the organization’s interests, both internally and externally.
Gartner “Innovation Insight for ModelOps”, Farhan Choudhary, Shubhangi Vashisth, Arun Chandrasekaran, Erick Brethenoux, 6 August 2020
ModelOps and MLOps Resources
In-depth resources to help you Scale and Govern your Enterprise AI initiatives with post development Model Life Cycle Automation
ModelOps Technical Masterclass Series
ModelOps Essentials Guide
ModelOps RFP Template
ModelOps includes MLOps
“ModelOps refers to the operationalization of all AI models and includes MLOps that deals with the operationalization of ML models”
“Use Gartner’s 3-Stage MLOps Framework to Successfully Operationalize Machine Learning Projects”, Shubhangi Vashisth, Erick Brethenoux, Farhan Choudhary, Jim Hare, July 2, 2020
Many large enterprises struggle to scale AI. Why?
Number of Models
The rapid and ongoing innovation in the data & analytics space leads to complexity unmanageable for even the most expert IT teams.
Adhering to strict and ever-increasing model regulatory requirements becomes more difficult as the use of AI expands across industries.
Ineffective collaboration across teams that need to work well together can make scaling difficult or impossible.
ModelOps Explained in 2 minutes
ModelOps is the systems and processes that automate the deployment, monitoring, governance, and continuous improvement of data science models running 24×7 within the enterprise’s most critical business processes and applications.
How do industry leaders drive AI at scale?
Enterprises drive AI into core processes at scale by focusing on three areas:
Leaders understand that deploying models into mission-critical applications requires them to run 24×7, without fail, with the same operational controls, tooling, and automation that support other technologies.
Leaders fully automate ModelOps processes, from deployment through monitoring and governance, to effectively manage a model within business SLAs and eliminate manual processing, reducing risk, cost, and model time to business.
ModelOp Solutions: built to help large enterprises address these challenges.
Designed to meet the needs of data scientists, IT, and business leaders. Backed by our proprietary software, ModelOp Center, and our expertise in data science, data engineering, infrastructure, software, and business transformation.
Align leadership with a ModelOps Assessment of your current state against best practices.
Speed to Value
Put 1-2 priority AI Models in Business, while designing foundation ModelOps capabilities. Delivered on ModelOp Center.
Deploy an Industrialized ModelOps program across the enterprise, customized to the specific requirements of the business. Delivered on ModelOp Center.
ModelOp Academy provides workshops, education and training to build awareness and develop core ModelOps skills and capabilities.
Explore the Impact of ModelOps
We have the experience and solution to help you harness the power of AI/ML at scale that will boost your core processes. Let’s create a unique solution together.
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.