Automated Commercial Environment (ACE)
Custom and Border Protection (CBP) Digital Services V
There were 6 main areas of scope included in this contract:1) Section 321 Entries U.S. Customs and Border Protection initiated this project in order develop, test, enhance performance, facilitate production support and operations & maintenance of Section 321 shipments that contain Partner Government Agency data. It was critical to maintain the performance and high volume of processed entries (> 1M) per day and guarantee system stability and not impact the flow of cargo.2) Broker Management ACE User Fee Automation Support as part of the Revenue Modernization effort recommended by Commercial Customs Operations Advisory Committee and other trade stakeholders, such as the National Customs Brokers & Forwarders Association of America to automate the collections of broker
triennial fees, license fees, and user fees in ACE. 3) Antidumping and Countervailing Duties (AD/CVD) Portal CBP Office of Trade and the Department of Commerce (DOC)Office of Enforcement and Compliance initiated this project with the objective of providing development, testing, production support and operations & maintenance AD/CVD application within ACE. The requested fixes and improvements significantly improved operations for DOC,CBP and the entire trade community through provision of more complete and accurate information on an AD/CVD duty case and company-specific basis. The work focused on delivering a cutting edge, modern architecture application that allow both agencies to meet their mission critical objectives.4) Enhance Agriculture Programs and Trade
Liaison(APTL)workspace within International Trade Data System to better communicate with USDA’s Arm system, integrate with CBP’s Document Management System.5)APTL Secure Flows systems interface enhancements goal is to automate paper process for phytosanitary and veterinary health Certificates in order for Agriculture Specialists to facilitate trade. The enhancements removed paper from the importation process in an effort to create efficiencies for shipments arriving at the border and reduce fraud. This allowed certificates to be electronically submitted and authenticate the validity of each certificate.6)This team was asked by CBP OIT to support an Innovation lab initiative on Machine Learning by prototyping and integrating new technologies to improve core functionalities of ACE. The team determined that a need related to the Harmonized Tariff Schedule(HTS)would be a great area to leverage machine learning. Based on that the team built a HTS To Text protype using machine learning to battle fraudulent classification of HTS in ACE. Harmonized Tariff Schedule is a system used to classify goods entering the United States. The prototype used a hybrid of a neural network and a search engine to perform a semantic search.