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Purchase Order OCR is an advanced technology that automates the process of data entry from purchase orders, invoices, and other business documents. OCR stands for Optical Character Recognition, which refers to the ability of a computer to recognize and interpret text from scanned images. Purchase Order OCR uses this technology to extract data from purchase orders in electronic format and convert it into machine-readable data. This speeds up the process of entering data into a system, reduces errors, and improves accuracy.
Purchase Order OCR helps businesses to eliminate the need for manual data entry, which can be time-consuming and error-prone. Purchase Order OCR also helps to ensure compliance with regulatory requirements, as it ensures that all data is captured and stored accurately. Additionally, it provides real-time visibility into the purchase order process, allowing businesses to track their purchases, inventory, and finances more efficiently. Ultimately, Purchase Order OCR is essential for any business looking to accelerate operations and stay competitive in today’s fast-paced business environment.
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Veryfi OCR APIs are pre-trained on hundreds of millions of documents for Day 1 Accuracy™.
Veryfi automatically provides: vendor enrichment, business ID lookup, document categorization, line item expansion & categorization, and due date calculation.
Enable 3-way matching by accurately extracting line item details in invoices, POs, bills of lading, and other documents in your AP workflows and procure-to-pay lifecycle.
Veryfi RESTful APIs return formatted JSON with consistent labels for extracted data, so your team can easily integrate Veryfi into your enterprise apps.
OCR APIs with Day 1 Accuracy™ for data extraction of purchase orders, invoices, and other financial documents.
Mobile framework for adding capture technology to your mobile expense, payment, ERP, and supply chain apps.
Integrate Veryfi with just a few lines of code, liberating your team to stay focused on building industry-leading customer experiences.