Based on Offering the market is divided into two segments: Platforms and Services. In 2024, the platforms segment dominated the market. Model complexity increases as more and more businesses use cutting-edge AI approaches. Because of this complexity, efficient development, deployment, and monitoring procedures require strong ModelOps platforms. Moreover, the requirement for continuous integration and continuous deployment (CI/CD) capabilities is fueled by the move toward agile approaches in software development. Rapid AI model deployment and iteration are made possible by ModelOps platforms, which improve response to shifting business needs.

Based on Deployment the market is divided into two segments: Cloud and On-Premises. In 2024, the market with the biggest revenue share was the cloud category. Because cloud-based ModelOps systems can scale resources up or down in response to demand, more and more organizations are implementing them. Businesses are able to effectively handle varying workloads thanks to this flexibility. Additionally, as compared to on-premises systems, cloud deployment lowers the overall cost of ownership. By using pay-as-you-go pricing structures, organizations can save upfront capital expenditures and allocate resources more effectively. Additionally, the cloud environment speeds up the deployment of ModelOps solutions, allowing businesses to respond to market demands by deploying models sooner. Sustaining a competitive edge requires this agility.

Based on Model the market is divided into six segments: ML Models, Graph-Based Models, Rule & Heuristic Models, Linguistic Models, Agent-Based Models and Others. In 2024, the ModelOps industry's highest revenue share was held by the ML models category. Predictive models perform better and are more accurate because to ongoing advancements in machine learning algorithms, which increases their suitability for a range of applications. Furthermore, strong machine learning models that can effectively handle and extract insights from massive datasets are required due to the exponential expansion in data created across multiple sectors. Better strategic planning is made possible by machine learning models that can predict trends, customer behavior, and operational hazards, which are also becoming more and more necessary as predictive analytics gains traction.

Based on Application the market is divided into ten segments: Customer Service & Virtual, Assistants, Robotics & Automation, Healthcare, Financial Services, Security & Surveillance, Gaming & Entertainment, Marketing & Sales, Human Resources, Legal & Compliance and Others. In terms of market revenue share, the Continuous Integration/Continuous Deployment (CI/CD) category held the biggest position in 2024. In order to improve operational efficiency and hasten the deployment of machine learning models, organizations are increasingly implementing CI/CD processes. This methodology facilitates faster iterations and more frequent updates, allowing teams to react quickly to evolving business requirements. By encouraging cooperation between data scientists, developers, and operations teams, the CI/CD architecture cultivates a continuous improvement culture. Organizations can improve project outcomes by reducing silos and streamlining procedures through workflow integration.

Based on Vertical the market is divided into eight segments: BFSI, Retail & E-Commerce, Healthcare & Life Sciences, IT & Telecommunications, Energy & Utilities, Manufacturing, Transportation & Logistics and Others. In 2024, the ModelOps industry's highest market revenue share was held by the BFSI segment. The BFSI industry must have strong governance and compliance structures because of the strict regulations it must adhere to. Organizations can efficiently manage risk and guarantee compliance with these laws by implementing ModelOps solutions. ModelOps adoption is driven by the need to increase operational efficiency and reduce procedures. Businesses can shorten the time it takes for new financial services and products to reach the market by automating model deployment and monitoring.

In 2024, North America was in the lead. Both the United States and Canada have strict laws, especially in areas like healthcare and BFSI. ModelOps frameworks are crucial for assisting companies in meeting AI model compliance standards while guaranteeing accountability and transparency.

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The market for ModelOps is very competitive. Continuous investment in research and development is evident, with a focus on integrating advanced features such as automated monitoring, governance, and compliance to meet evolving industry demands. Some of the prominent players in Global ModelOps Market are Amazon Web Services Inc., Cloud Software Group Inc., Cloudera Inc., DataRobot Inc., Domino Data Lab Inc., Google Cloud, Hewlett Packard Enterprise Development LP, IBM Corporation, Microsoft and SAS Institute Inc.

In July 2024, Teradata, a cloud analytics platform supplier, has teamed with DataRobot, Inc., an open AI platform provider, to integrate DataRobot's AI Platform with Teradata's ClearScape Analytics and VantageCloud. This integration aims to help businesses maximize their AI potential by increasing flexibility and alternatives for designing and scaling safe, efficient AI models.In May 2024, Microsoft has announced GPT-4o, OpenAI's new model for Azure AI. This multimodal model has audio, visual, and text capabilities, allowing for generative and conversational AI functionality. GPT-4 is now previewable in Azure OpenAI Service, and it supports text and image inputs.

In May 2024, Google Cloud has released Generative AI Ops, a new service offering. This offering, available through Google Cloud Consulting or Google Cloud's partner ecosystem, is intended to help enterprises transform their generative AI prototypes into production-ready solutions. It supports critical areas such as security, model adjustment, feedback, and optimization.