Case Study: Fero Labs achieves higher production and quality with Microsoft Azure

Machine learning startup helps heavy industries boost production, increase quality

Fero Labs, a small U.S.-based industrial machine learning company, needed a scalable way to process massive factory sensor data and improve production and product quality across heavy industries like auto, chemical, oil and gas, and steel. The company turned to Microsoft Corporation and its Azure platform to avoid the cost and complexity of building the solution on-premises while supporting enterprise customers.

Using Microsoft Corporation’s Azure and Azure Stack, Fero Labs delivered a flexible machine learning platform that analyzes sensor data, predicts failures, and explains the factors affecting KPIs. In one oil refinery case, the solution predicted pipe temperatures three weeks ahead with 91% accuracy, compared with 43% for classical Six Sigma methods, helping reduce shutdowns and contributing to a projected USD 4 million increase in annual revenue.

Fero Labs

Berk Birand

Chief Executive Officer