Verusen Debuts AI-Powered Supply Chain Business Intelligence

The system streamlines collaboration between procurement and operations.

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CHICAGO — Verusen on Tuesday announced the launch of its AI-powered Supply Chain Business Intelligence capability for its Verusen Trusted Material application.

Verusen will showcase the new offering at ProMat Chicago, March 20-23, at ProMat Booth #S2684.

The new Business Intelligence capability provides procurement and operations teams, from senior management to front-line workers, with data-driven insights in the form of actionable and interactive reports and dashboards. Users gain increased clarity and materials visibility to view, filter, export, and share reports enabling decision-making that leads to improved business performance and bottom-line savings.

“In 2023, supply chains continue their transition past the pandemic world, embracing advanced technologies,” said Paul Noble, CEO and founder of Verusen. “However, data is still siloed, and collaboration between operations and procurement teams is challenged by limited visibility, data staleness, and manual efforts to collect and share data. Working in disparate silos, procurement and operations teams are frequently in conflict, with traditionally misaligned goals limiting execution at scale.

"We’re thrilled to be able to empower these groups with visual and actionable reporting and analytics to drive alignment and add a new level of collaboration and strategic decision-making. Having these kinds of insights is critical to advancing business. Companies can now collaborate seamlessly, efficiently, and effectively across their enterprise supply network.”

With Verusen’s latest offering, customers and cross-functional teams can achieve improved data visibility and communications. Manufacturers can leverage Verusen’s platform to implement better decision-making for streamlined and strategic material management. They can interact, filter, and customize material reports to drive improved business outcomes — including inventory and risk optimization and tail spend analysis, without the need for data cleanses.

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