The U.S. Customs and Border Protection (CBP) is seeking industry input on artificial intelligence and machine learning tools to support analysis of border inspection images generated through its non-intrusive inspection (NII) systems.
In a request for information (RFI) posted on April 30, CBP said the initiative aims to reduce average inspection processing times while increasing the number of scanned vehicles and cargo entering the United States. The agency said the effort is intended to strengthen security, ease officer workload, and avoid slowing commerce.
CBP’s Office of Field Operations is focusing on large-scale X-ray imaging systems deployed across airports, seaports, and land border crossings.
According to the agency, the growing volume of scan data is exceeding human analysis capacity, increasing the need for AI-assisted anomaly detection and threat identification.
“The sheer volume of data generated by increased scanning can be overwhelming for human operators, necessitating innovative solutions to maintain efficiency and effectiveness. AI/ML models can be leveraged as tools to assist CBP employees with making better decisions faster, reviewing and synthesizing data, improving efficiency and learning from every new piece of information,” the RFI reads.
Areas of interest include contraband detection, manifest validation, image segmentation, risk scoring, and identification of suspicious vehicle modifications. Industry responses are due by May 30.