NextGen Supply Chain Conference Awards Recognize Companies Shaping Tomorrow’s Supply Chains

AutoScheduler.AI, an innovative Warehouse Orchestration Platform and WMS accelerator, has announced the company is named a winner in the Artificial Intelligence category of the NextGen Solution Provider Awards. The NextGen Solution Provider Awards honor up to four solution providers that have utilized NextGen supply chain technologies in a project implemented for a customer in the following categories: Robotics, Digital Transformation, Artificial Intelligence, and Predictive Analytics.

“We are proud to win this prestigious award for our AI-enabled technology that takes disparate data and converges supply chain activities to create plans that orchestrate campus operations for optimized efficiency prescriptively,” says Keith Moore, CEO of AutoScheduler.AI. “Our clients’ warehouses operate at peak performance.”

The NextGen Supply Chain Conference Awards recognize the companies shaping tomorrow’s supply chains with advances that are helping organizations navigate the complexities of the modern supply chain while also preparing them for success in the future. Winners will be presented their award at the conference which takes place in Chicago, October 21-23, 2024, at the Chicago Athletic Association.

Moore adds, “Our technology smooths warehouse operations by orchestrating and planning all activities in real-time on top of an existing WMS. It considers space, time, labor, dock doors, and more constraints to ensure that orders are fulfilled on time and in full. Clients gain efficiencies and value in their supply chains through optimized labor, schedules, touches, and inventory.”

AutoScheduler’s AutoPilot converges disparate data to orchestrate supply chain activities and optimize campus operations. By integrating data from WMS, yard management systems, ERP, visibility systems, and production schedules, it creates a unified view of operations. Utilizing operational twin technology, AutoPilot predicts future states by analyzing current conditions and planned activities across systems. It employs complex mathematics, AI, and optimization techniques to determine the most efficient use of capacity. This approach optimizes activity systems, prescribes event sequences, and creates a feasible operational schedule, minimizing touches and labor while maximizing service levels.