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whitePaper | October 11, 2021

AI forms the bedrock to help organizations unlock business value from the deluge of unstructured information. Improving operational efficiency by extracting structured data from unstructured documents enables organizations with faster and contextrich decision-making to adapt and thrive in the new normal.

whitePaper | November 1, 2021

Robotics, automation, Internet of Things (IoT), and data are not new in manufacturing. Manufacturing is one of the most data-rich and first industries piloting artificial intelligence at the edge. It’s been estimated, however, that about 95% of all industrial data goes unused. The reason? Legacy equipment and operational systems that tend to be proprietary and siloed are incapable of communicating with each other.

whitePaper | July 28, 2022

Before the pandemic, the path to AI adoption used to be slow and steady. According to the survey of industryleading firms, only 48% of companies deemed AI and Big Data a source of innovation. In 2021, this number has climbed to almost 65 percent.

whitePaper | July 21, 2020

Back in 2016, the most popular app download on Christmas Day was Fitbit, dominating Apple’s App Store. The rapid adoption of Fitbit and other wearable fitness trackers has underpinnings in psychological motivation theories. Realtime data monitoring provides a powerful incentive that is capable of changing human behavior. Since 2016, the wearable technology market has continued to evolve, including the acquisition of Fitbit by Google, which was announced in November 2019.

whitePaper | September 28, 2022

Architecting IT infrastructure has never been more challenging than it is today. Many enduser workloads, such as semiconductor design, autonomous driving development, and life sciences and healthcare are growing more complex every day. With that complexity comes growing demand on IT.

whitePaper | November 15, 2019

The demands of running global supply chains can be unrelenting – perfection of operations, innovation in support of lastmile delivery, and assurances of sustainability in the pursuit of delivering the “perfect order” as promised. Now, transportation companies face the additional challenge of sharpening their core competencies while increasing the pace of innovation, adapting emerging technologies, and sharing data with their customers to improve transparency and efficiency. Long characterized by capital-intensive assets, forward-looking cargo companies are turning their attention to the data that comes from their own assets and infrastructure as well as from their customers. It is a complex transition, one that requires knowledge-based labor, automation, and predictive planning to turn transportation companies into digital platforms.