Hexaware Positioned as a Visionary in the 2026 Gartner® Magic Quadrant™ for Custom Software Development Services
Hexaware Positioned as a Visionary in the 2026 Gartner® Magic Quadrant™ for Custom Software Development Services
Gartner, Magic Quadrant for Custom Software Development Services, By Jaideep Thyagarajan, Ryan McKinney, Nathan Davie, 28 September 2026. Gartner and Magic Quadrant are trademarks of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Hexaware.
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– Hexaware’s MLOps automation framework brings structure to machine learning models in production.
– The framework adds model drift detection and CI/CD tools for machine learning workflows.
– Automated retraining and monitoring reduce the need for constant hands-on model management.
– MLOps automation and modern lifecycle tools get a one-stop overview in this quick reference.
Managing machine learning (ML) in production can be complex, especially when dealing with changing data and the risk of models becoming outdated. Our MLOps automation framework brings structure to these processes, adding tools like model drift detection and CI/CD for machine learning.
Automate Model Retraining and AI/ML Lifecycle Management
With an end-to-end MLOps solution, you can automate key parts of the AI/ML workflow. This includes automated model retraining, monitoring models for drift, and handling updates without manual intervention.
Here, automation ensures your models stay reliable and reduces the need for constant hands-on management.
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Need a quick overview of how AI/ML lifecycle automation and modern MLOps tools work? Learn more about our MLOps automation framework as a one-stop solution.