OCR for Invoice Launches AI Tool to Automate Invoice Data Extraction for AP Teams

OCRforInvoice.com introduces an AI-driven OCR platform that extracts invoice data from PDFs and scans, integrates with spreadsheets and ERPs, and helps teams cut processing time by over 90%.

Washington, July 15, 2025 — OCRforInvoice.com has officially launched its AI-powered OCR platform built to automate invoice processing for accounts payable teams. The tool extracts line items, invoice numbers, and key fields from PDFs, scanned documents, images, and emails. No templates or setup are required.

The system handles different vendor formats and lets users define custom rules for data extraction. Results can be exported directly to Excel, Google Sheets, QuickBooks, or ERP systems. This helps teams save time, reduce errors, and improve accuracy.

OCRforInvoice.com is HIPAA compliant and uses AES-256 encryption to secure all data. Customer files are not used for model training, and data processing agreements are available to ensure full compliance.

Early users have reported major gains in efficiency. Some teams now process invoices in minutes instead of hours. With flexible pricing starting at 1,000 pages per month, the platform supports businesses of all sizes.

“Manual invoice entry slows down finance teams and creates unnecessary risk,” said press contact Julia Brown. “OCRforInvoice.com solves that by making invoice data capture fast, accurate, and hands-free.”

About OCRforInvoice.com

OCRforInvoice.com is an AI-powered OCR platform that automates invoice data capture and simplifies accounts payable workflows. It extracts structured data from unstructured invoice formats and exports it to spreadsheets or accounting tools, helping teams scale without adding headcount.

Media Contact

Organization: OCRforInvoice.com

Contact Person: Julia Brown

Website: https://www.ocrforinvoice.com/

Email:
julia@ocrforinvoice.com

State: Washington

Country:United States

Release id:30725

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OCR for Invoice Launches AI Tool to Automate Invoice Data Extraction for AP Teams

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