An OCR alternative that actually understands invoices.
OCR reads characters. Harold understands documents — who sent them, what the fields mean, whether the data is correct, and where it needs to go.
The problem with OCR for invoice processing
OCR was built to digitise text. Invoice processing requires something more — understanding, validation, and business logic.
Character accuracy without context
OCR reads characters — it doesn't understand that 'Inv No' and 'Invoice Number' and 'Your Reference' all mean the same thing on different suppliers' documents.
No validation layer
OCR hands you characters. Whether those characters are the right value in the right field is entirely your problem to check.
Format sensitivity
Move a field 2mm on a template and OCR breaks. Scanned at a slight angle? Quality degrades. Handwritten amendments? Ignored.
No supplier intelligence
OCR treats every invoice from every supplier as a new problem. There's no learning, no memory, no improvement over time.
What Harold does differently
Understands supplier context
Harold builds a profile for each supplier. It learns that Supplier A always puts the PO reference in the footer as 'Your Ref', and Supplier B encodes it in the subject line. OCR can't do that.
Validation before it leaves Harold
Harold's Rules Engine checks every extracted document against your business logic — mandatory fields, VAT rate validation, GL code assignment, KeyMatch against your supplier list. Data that fails your rules doesn't reach your ERP.
Format-resilient extraction
Harold uses vision AI, not pixel-level character recognition. A scanned invoice at a slight angle, a PDF with non-standard fonts, a handwritten note on a printed invoice — Harold handles all of it.
Improves over time
Each correction you make in Harold trains the supplier profile. The more invoices you process, the more accurate the extraction. OCR doesn't get better.
Ready to move beyond OCR?
Start free, no credit card required. See the difference in your first document.
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