Also known as: Optical character recognition, Automatic document reading
Technology that converts printed or handwritten text in scanned documents, photographs, or PDFs into editable, processable digital text, widely used in international trade to extract data from invoices, bills of lading, certificates, and other customs documents.
OCR (Optical Character Recognition) is a technology that digitizes text contained in images, scans, or non-editable PDF files. In the customs context, it is used to automatically extract key data from documents such as commercial invoices, bills of lading, certificates of origin, and packing lists, eliminating manual data entry and reducing transcription errors.
Camtom integrates OCR with artificial intelligence in Docs to not only read text but interpret document context: automatically identifying fields such as supplier, merchandise description, value, Incoterm, and suggested tariff code.
Modern OCR, powered by neural networks and deep learning, overcomes traditional OCR limitations by handling documents with inconsistent formats, low image quality, overlapping stamps and signatures, and variable typography common in international trade documents.
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The application of artificial intelligence algorithms—machine learning, natural language processing, and computer vision—to automate and optimize foreign trade processes such as tariff classification, document review, and customs risk detection.
DocumentsCOVE (Electronic Value Voucher)
Electronic document that certifies the declared value of goods in the customs declaration, transmitted through Mexico's VUCEM system.
DocumentsCommercial Invoice
Document issued by the seller/exporter describing the goods sold, their price, terms of sale, and details of the parties involved.
TechnologyCustoms API
An application programming interface (API) designed to connect foreign trade systems—ERPs, TMSs, e-commerce platforms—with customs services such as tariff classification, duty calculation, document validation, and customs entry transmission programmatically.