Special study
The Total Economic Impact™ of Red Hat Hybrid Cloud Platform for MLOps
Cost savings and business benefits of Red Hat OpenShift for operationalizing AI/ML in financial services
Total Economic Impact™ study reveals 210% ROI for Red Hat MLOps customers
In today’s modern enterprise, artificial intelligence (AI) and machine learning (ML) have become critical business tools for industry leaders. However, organizations frequently experience challenges as AI/ML use is scaled from tactical or experimental use cases to enterprise-wide adoption.
This commissioned study conducted by Forrester Consulting on behalf of Red Hat—which revealed a 210% ROI over 3 years for a composite organization—is built on customer feedback and provides industry leaders with a framework to evaluate the potential financial impact of enabling Machine Learning Operations (MLOps) on Red Hat for their organizations.
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Key findings
What customers say about Red Hat Hybrid Cloud Platform for MLOps
We have models for marketing, churn models, credit card churn models, and ATM cash optimization models. We have reduced the time-to-market for use cases by one to two months.
Before, when new data scientists were added to our team, they had to wait for notebooks to be deployed on bare metal servers for them. Now, with Kubernetes, we can dynamically add more notebooks. The data science team is no longer dependent on any other team to request new infrastructure.
There were different processes that people were following. You have some folks doing things on the cloud, some on-prem —different ways that people were achieving the same objectives. Consolidating that to using [Red Hat OpenShift] helps us realize cost savings [in licenses, hardware, and cloud computing costs].
Reference customers shared that Red Hat Hybrid Cloud Platform for MLOps
The Total Economic Impact™ of Red Hat Hybrid Cloud Platform for MLOps Table of Contents
- Executive Summary
- The Red Hat OpenShift For MLOps Customer Journey
- Analysis of Benefits
- Financial Summary