How AI Reads and Extracts Data from Invoices

What AI is actually doing

Modern invoice AI uses a combination of optical character recognition (OCR) to read text from PDFs and images, plus large language models to understand context. The LLM doesn't just find the number after '£' — it understands that 'Net amount', 'Subtotal', 'Exc. VAT', and 'Before tax' all mean the same thing, even when formatted differently across different suppliers.

What AI extracts from a typical invoice

• Supplier name and address (even partial or informal names)
• Invoice number / reference
• Invoice date and due date
• Line items with descriptions, quantities, unit prices
• Net amount (ex. VAT)
• VAT amount and rate
• Gross total (inc. VAT)
• Payment terms (e.g. '30 days net')
• Bank details (sort code, account number, IBAN)
• Purchase order reference if present

Where accuracy is high vs. where to double-check

How InboxBill handles low-confidence extractions

Every field has a confidence score. Fields below the threshold are highlighted in the review UI so you can quickly correct them. Over time, corrections teach the system about your specific suppliers — improving accuracy for recurring invoices.