10/09/2025 | Press release | Archived content
When package dimensions are missing or wrong, it doesn't just slow down label printing-it throws off the entire delivery strategy.
This gap in weight and dimension data for shipments prevents us from being able to accurately compare carrier rates or choose the best route to the extent we'd like to for clients.
Package Predictor fills in the gaps by learning how products are actually packaged-not theoretical predictions based on how they're measured in product catalog data.
It looks at how these items have been shipped before, both for single-SKU and multi-SKU shipments where items are combined into a single package and then uses those historical patterns to predicts the package size.
With that info, we can now pick the best shipping method-picking the best balance between speed and cost automatically. No more overpaying because a package was misclassified or choosing a slower carrier when faster was just as affordable.
On the warehouse floor, Package Predictor cuts out repetitive work. No more needing to enter the same weights and dims data where it's missing for SKUs over and over again. Predicted dimensions flow directly into the label printing process, helping teams move faster with automation.