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What is PO Matching? And how to automate it?

Nanonets

MS-Word documents), data entry files (e.g., MS-Word documents), data entry files (e.g., MS-Excel files), structured XML documents from Electronic Data Interchange (EDI), PDFs and image files, and sometimes as hard copy documents. that can lead to loss of productivity and trust. Figure 4: OCR based data retrieval.

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Best Accounts Payable Software of 2023

Nanonets

Schedule a Demo auto-collect documents into your AP workflow The top 17 AP software tools Find below, a list of the top 17 accounts payable software platforms that are available off-the-shelf today, and their specialized features. Looking to automate your manual AP Processes?

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How to Use AI in Bank Statement Processing

Nanonets

Set up rule-based workflows to identify and remove any duplicate entries and human review for complex or ambiguous transactions. Regularly analyze reasons for variances (for eg: format differences, fraud, duplicate records) Discrepancy identification During reconciliation, any mismatches are flagged for further review.

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BPO automation software: A quick guide

Nanonets

Take, for instance, omnichannel call centers or document processing. Seamless integration will enable smooth data flow and avoid duplication of effort. Look for responsive support channels and resources such as documentation, tutorials, and training materials. This is where BPO automation software comes into play.

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What is two-way matching and how does it work?

Nanonets

Invoice is a legally binding document that is issued by the vendor to the purchaser along with or after the delivery of the product/service to the customer. Manual consolidation is prone to errors, leading to issues like overpayment, incorrect payments, and invoice duplication, ultimately causing productivity and trust losses.

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How to automate data extraction in healthcare: A quick guide

Nanonets

Healthcare data extraction systems capture and extract crucial information from a variety of healthcare documents—patient records, insurance forms, lab results, billing information, regulatory compliance documents, and more. million new frontline healthcare workers due to inefficient data extraction from healthcare documents.