Industrila IoT firm Bsquare Corporation said it is collaborating with Amazon Web Services (AWS) to meet the increasing demand for IIoT solutions. Bsquare has selected AWS as its preferred cloud services provider and is leveraging AWS to expand new offerings around DataV, a suite of edge-to-cloud IoT services and software designed to improve uptime, manageability, and performance of enterprise assets.

“Bsquare has a long track record of success developing solutions running on AWS that help industrial businesses reach their IoT goals,” said Acting Bsquare CEO, Kevin Walsh. “We also share the same commitment to constant innovation that is necessary to drive digital transformation across a variety of enterprise and industrial markets. As a result, we are pleased to be able to collaborate with AWS as we work together to develop more advanced solutions for our customers.”

Since being named an AWS IoT Competency Partner in the AWS Partner Network (APN) in 2016, Bsquare has increasingly leveraged AWS IoT service offerings, including AWS Greengrass, AWS IoT Device Management and AWS IoT Analytics for customer deployments. In just one example, a Fortune 100 global brand is leveraging DataV on the AWS infrastructure to enable IoT device and content management for tens of thousands of IoT devices across North America and Europe in order to simplify and automate content updates and ensure device compliance. In another joint example, PACCAR, parent of Kenworth, Peterbilt, and DAF heavy duty trucks, is using DataV to adaptively diagnose truck failures in order to reduce time-to-repair and improve first-time-fix ratio.

“By leveraging AWS IoT services, Bsquare's DataV suite can help customers accelerate time-to-value versus customizing solutions in-house,” said Joshua Hofmann, Director, AWS Partner Ecosystem, Amazon Web Services, Inc. “We look forward to working with Bsquare to help our customers achieve additional IoT success at a faster pace.”

The DataV IoT software and services solution is designed to help businesses translate insights generated by industrial assets into critical operational improvements. By gathering key device data, and applying rapid data analytics and machine learning, businesses can improve asset uptime, reduce costs, increase revenue and more.