ProvisionAi Sustainable Supply Chain

91%: that is the number of underloaded trucks on US highways.

Why? Because maximizing payload while designing axle-legal, damage-free loads is hard.

The benefits of using AutoO2 (Automatic-Order-Optimization), an optimizing load builder, are less carbon, lower cost, and less congestion. 50%: that is the damage reduction that AutoO2 generates, along with a 15% increase in warehouse labor productivity through guiding order selectors to build stable, damage-free pallets and stack them neatly in the truck The AutoO2 works in both planning and execution, so what is planned is what is executed.

Good companies plan; great companies execute.

AutoO2 leverages machine learning to optimize shipments, respect axle weight, and mitigate damage.

It follows product—and customer-specific loading rules and seamlessly integrates with existing systems.

Riviana Foods saw “over $ 1 million in savings” when they implemented AutoO2.

Riviana, a leading rice company, had problems maximizing payload and suffered “reloads” as forklift drivers didn’t make the loads axle-legal.

With AutoO2, Riviana can ensure that all truckloads leave their facility legally and at full payload.

Notably, the learning curve for loaders was substantially reduced as they can now follow load diagrams.

The successful implementation of AutoO2 saves Riviana cost and carbon.