QAD Unveils Enhanced AI Classification Features at the 2024 Gartner® Supply Chain Symposium/Xpo™

Today, a prominent provider of cutting-edge manufacturing and supply chain solutions in the cloud unveiled significant enhancements to its Import Management solution at the Gartner Supply Chain Symposium/Xpo™. QAD Global Trade and Transportation Execution (GTTE) now feature an advanced product classification tool driven by artificial intelligence (AI).

Product classification, crucial in international trade, involves assigning a commodity code to items based on the Harmonized System of the World Customs Organization. This code aids customs authorities in processing imports and exports, along with assessing duties and taxes.

Carter Lloyds, Chief Product and Marketing Officer at QAD, emphasized, “Product classification is arguably the most important data element in an international trade transaction, but also one of the most time-consuming and complex tasks that trade professionals must undertake.” He further highlighted QAD’s commitment to a ‘Pragmatic AI’ approach, leveraging AI to assist users in problem-solving.

QAD’s machine learning algorithm streamlines classification by comparing data against previously classified products, providing a list of recommended products and their corresponding HS codes based on similarity. This method expedites classification by starting with a known HS code of a similar product. User confirmation of the recommended HS code refines the system’s learning process for future comparisons.

“This will fundamentally change the way product classification is traditionally performed today by allowing the importer to ‘work backwards’ from an established product classification, thus saving companies considerable time while promoting classification speed, accuracy, and consistency,” added Lloyds.

For more information on QAD solutions and how they can enhance your transformation journey, visit qad.com.

(GARTNER and SUPPLY CHAIN SYMPOSIUM/XPO are trademarks of Gartner, Inc. and/or its affiliates, used under permission. All rights reserved.)

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