Turn any document into structured data.

OCR (Optical Character Recognition) software extracts text and data from scanned documents, photos and PDFs so it can be searched, filtered or fed into other systems. In business, it’s most commonly used to automate invoice and receipt data entry, digitise contracts, process bank statements, and capture forms — replacing manual typing with structured, queryable data.

Traditional OCR uses pattern matching and zone-based templates: a vendor template tells the software where to find each field. It breaks the moment a layout changes. AI OCR (like Zerentry) uses large language models that understand context, so it reads any layout out of the box, supports mixed languages, and handles handwriting — without any templates to maintain.

Zerentry processes invoices, receipts, bank statements, contracts, purchase orders, delivery notes, credit notes, expense reports and any structured business document. It supports PDF (digital or scanned), PNG, JPG, JPEG, HEIC and TIFF.

Yes. Zerentry handles 50+ languages out of the box, including mixed-language documents (for example a French invoice with English line-item descriptions). No per-language configuration is required — the same pipeline processes any language.

Traditional OCR cannot. Zerentry’s AI OCR has built-in handwriting recognition, which is useful for physical receipts, delivery notes, expense forms and any document with handwritten annotations. Handwritten fields get a confidence score so you can review them quickly.

Zerentry achieves 95%+ field accuracy on structured business documents, compared to 70-85% for template-based OCR tools. Every extracted field comes with a per-field confidence score so reviewers focus only on uncertain values, and accuracy compounds over time as the system learns from corrections.