Paccurate is the leading carton optimization software platform. When fulfillment costs rise, having perfectly packed shipments doesn’t just make for happier recipients, it’s a competitive advantage. Paccurate is an API-first cartonization solution. When provided with item and box dimensions, Paccurate generates efficient packing instructions for humans or box-on-demand machines. Paccurate takes a different approach than legacy WMS or other cartonization providers. Rather than focusing on cubic volume reduction alone, Paccurate optimizes for costs directly. From materials, labor, and even obscure breakpoints in your unique carrier rates, PacAPI finds the optimal way to pack every order.
PacSimulate can simulate millions of shipments to determine the ideal box mix for your operation, predict the impact of box-on-demand machines, and evaluate the downstream impact. Optimizing parcel fulfillment both inside and outside the box, Paccurate helps ship sustainably while reducing costs.
Paccurate Case Study: Daily HarvestDaily Harvest had a change in their product set which led to a disruption in their pre-existing cartonization algorithm. This resulted in substantial transportation cost overages. Since implementing Paccurate, they've reduced transportation spend and reduced corrugate by 7% across their operation.
Paccurate Case Study: Hunter DouglasHunter Douglas was using manual processes to cut custom boxes for their unique orders. The DIM and overweight fees were becoming excessive, increasing transportation costs by almost 15%. Since implementing Paccurate, Hunter Douglas has reduced packaging errors and optimized their box-on-demand solution for more control over the packing process.
Paccurate Case Study: Lionel TrainsLionel Trains was adding labor to keep up with seasonal demand. Using their best guess to determine the best size box to ship orders resulted in an increase in shipping costs. Paccurate's cartonization API helped Lionel Trains increase packing and labor efficiency as well as reduce shipping costs by 10%.
