These documents are example RFPs for addressing the functional requirements of ModelOps. These have been created as a result of interviews with several industry experts and analysts. ModelOps is a key capability that is required for successful AI/ML model operations across the enterprise once models have been developed.
Industry experts and analysts now recognize that model development and model operations are different disciplines, requiring different capabilities, tools and even teams.
Gartner defines ModelOps as:
Artificial intelligence (AI) model operationalization (ModelOps) is a set of capabilities that primarily focuses on the governance and the full life cycle management of all AI and decision models. This includes models based on machine learning (ML), knowledge graphs, rules, optimization, natural language techniques 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 operationalizing all AI and decision models.
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.