What is an AI receipt scanner and OCR?
How those two relate to each other?
OCR is the technology that converts text from images (like receipts) into machine-readable digital data.
AI receipt scanner enhances OCR by applying artificial intelligence to recognise patterns, detect anomalies, and improve data extraction accuracy over time.

Key principles of AI and OCR
OCR (Optical Character Recognition) is a cornerstone of modern expense management, enabling the automatic conversion of printed or handwritten text on receipts into digital, searchable data. But with the evolution of artificial intelligence, the traditional OCR has become even more powerful.
AI receipt scanners build upon OCR by using machine learning and advanced algorithms to better understand, interpret, and validate receipt data – delivering even greater accuracy and intelligence in expense automation.
Application:
Together, OCR and AI receipt scanning automate the capture, validation, and classification of expense data from receipts and invoices, making expense reporting faster and more reliable.
How it works:
-
Capture
Employees simply take a picture or upload photo of a receipt or invoice using their mobile expense app. -
AI and OCR Extraction
OCR extracts the text while AI interprets the structure, identifies key fields (like merchant, amount, date, currency), and even flags duplicates or inconsistencies. -
Integration
The processed data is automatically fed into the expense management system, pre-filled into reports, and matched against company policies.
Benefits of combining AI and OCR:
- Efficiency - Eliminates manual entry and speeds up the expense submission process.
- Accuracy - AI improves OCR by learning from past receipts, reducing data errors.
- Smart Validation - AI can detect duplicate receipts, unusual spending, or missing data.
- Faster Reimbursements - Data is processed instantly, reducing administrative delays.
- Mobile Convenience - Submit receipts from anywhere, anytime.
- Compliance - Ensures correct VAT extraction and alignment with policy rules.
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