What is ModelOps?

A critical capability to scale and govern enterprise AI

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ModelOps: a foundational capability for enterprise AI

Gartner “Assessing DevOps in Artificial Intelligence Initiatives”,  Carlton Sapp, 21 February 2020

Organizations continue to struggle getting their AI and data science models deployed to production and managed once they are there. ModelOps aims to reduce the burden of deploying and managing models in production.

Gartner “Assessing DevOps in Artificial Intelligence Initiatives”, Carlton Sapp, 21 February 2020

How do industry leaders drive AI at scale?

Enterprises drive AI into core processes at scale by focusing on three areas:

Model-Centric Approach

Leaders manage models as first-class enterprise assets, supported by a model-centric architecture to enable long-term, uniform deployment success independent from data science workbenches and execution platforms.

Operations-First Mentality

 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.

Automation

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.

ModelOps Defined

Model Operations (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.

Many large enterprises struggle to scale AI. Why?

Number of Models

Each business will need to manage hundreds of models to account for business process variations, personalization, and unique customer segments.

Technology Complexity

The rapid and ongoing innovation in the data & analytics space leads to complexity unmanageable for even the most expert IT teams.

Regulatory Compliance

Adhering to strict and ever-increasing model regulatory requirements becomes more difficult as the use of AI expands across industries.

Organization Silos

Ineffective collaboration across teams that need to work well together can make scaling difficult or impossible.

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.

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Get Started

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.

Scale

Deploy an Industrialized ModelOps program across the enterprise, customized to the specific requirements of the business.  Delivered on ModelOp Center.

Learn

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.

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