Powering tomorrow. Machine Learning goes electric.

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Client Objective

Requiring a high-voltage solution. The VP of Data and Analytics at an energy company needed help building machine learning operations (ML Ops) capabilities to supercharge advanced analytics to optimize the power grid. The stakeholders wanted these insights to be integrated into business applications and models that could be continuously measured, monitored, and improved. Plus, they wanted all these capabilities made available across the company.

Unique Challenge

Static knowledge. While the VP’s stakeholders had high hopes and even bigger expectations for scaling machine learning solutions – the team lacked the AI/ML leadership and expertise they needed.

Bespoke Solution

Scaling value with off-the-grid thinking. Unify developed an ML Ops architecture and implementation roadmap by working with the VP’s data team and other key leaders. The Unifiers designed an end-to-end ML solution for widespread usage that included everything from management to monitoring, automation, delivery, and governance.

Proven Impact

A bolt of speed and value. After partnering with Unify to design and implement ML Ops, the client was able to achieve ML at scale. The executed roadmap decreased the time to operationalize models from several months to just weeks. Now stakeholders have access to real-time ML algorithms and predictive analytics that enable operational insights and decision-making – keeping operational efficiency flowing like never before.

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Powering tomorrow. Machine Learning goes electric.