From Static Rules to Shipment-Level Intelligence: A 90-Day Operating Blueprint

Parcel networks have become more complex while many shipping decisions remain governed by static rules. Carrier portfolios may expand, data may improve, and dashboards may become more sophisticated, yet the final carrier/service choice can still depend on logic that changes only periodically.

The supplied Luma AI Select case study demonstrates the potential value of closing that gap. A global recommerce marketplace processing more than 25,000 labels per day through EasyPost deployed shipment-level AI service selection at label creation. The case study reports more than $2 million in annual savings, a 4–5% reduction in per-label cost, an increase in on-time delivery from 80% to 83%, and approximately 273,000 fewer late deliveries per year [1].