Operational machine learning at enterprise scale
Bring DevOps-like speed and agility to ML workflows with support for every stage of the machine learning lifecycle: from sandbox experimentation with your choice of ML/DL frameworks, to model training on containerised distributed clusters, to deploying and tracking models in production.
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How do we fast forward to the future of data science? Meet HPE Ezmeral ML Ops, which accelerates model deployment from years to months and is available as a service. It’s time to unlock the potential of your data and realise the possibilities of machine learning.
A CONTAINER-BASED SOLUTION FOR THE ML LIFECYCLE
Standardise processes across the ML lifecycle to build, train, deploy and monitor machine learning models.
Model Build
Model Training
Model Deployment and Monitoring
Collaboration
Security and Control
Hybrid Deployment
- 53increased profitability 1
- 52better customer experience 2
- 49better adoption of data science best practices 3
Technical videos
FASTER TIME TO VALUE FOR AI / ML
HPE provides data science teams with one-click deployment for distributed AI / ML environments and secure access to the data they need.

ADVISORY BOARD (OPTUM) USES BLUEDATA TO ACCELERATE BUSINESS OUTCOMES WITH AI AND ML IN THE ENTERPRISE
Advisory Board (Optum) deploys predictive analytics and machine learning on big data using the container-based platform from HPE’s BlueData team platform. Learn how they streamlined operations and cut costs while enhancing patient care in U.S. hospitals.
Challenge
Helping hospitals across the US translate their big data into actionable insights that deliver business value.
Solution
Deployment of distributed ML and analytics applications and for the separation of compute and memory from storage.
“BlueData has helped us to address these challenges with their containerised solution that has delivered faster time-to-insights, reduced our costs and freed up our staff to innovate. It’s paying big dividends for our organisation, and we look forward to continuing our journey together.”
Result
Data-driven insights needed to improve operational efficiency, reduce infrastructure costs and enhance patient care.