ModelOps platforms offer the following advantages for AI operations
Accelerated delivery of AI products to business users
Better alignment between business domain experts, datascience and engineering
Constant feedback on modeling outputs by business and/or operational experts
Governance and quality assurance of models and modeling outputs in conjunction with business domain experts
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:
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.
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.
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.
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.
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.