Practice Summary: Cainiao Enhances the Parcel Sorting Efficiency Through AI-Generated Delivery Zone Codes.

This article focuses on Cainiao Network’s development and deployment of an AI-driven system to enhance parcel sorting efficiency through automated generation of three-level delivery zone codes used by Chinese express logistics providers. Cainiao’s lightweight transformer-based model, called Transformer-mini, frames delivery zone code prediction as a multiclass classification problem using natural language processing techniques on customer-entered address text, achieving 98%–99% accuracy. Integrated into logistics management systems, this AI solution processes tens of millions of parcels daily for major providers such as STO Express and YTO Express, reducing manual labor costs by 3%–5% and improving sorting speed. The system addresses limitations of prior rule-based and geofencing methods by learning from large-scale historical data and handling address ambiguities, thereby optimizing last-mile delivery operations within Alibaba’s e-commerce ecosystem.