The Problem
Every business drowns in paper. Invoices, delivery notes, purchase orders, receipts — they arrive as PDFs, scans, photos, even faxes. Someone has to open each one, read it, type the data into an ERP. One invoice takes 3–5 minutes. Multiply that by hundreds per month.
The errors are invisible until they're expensive. A transposed digit in a tax ID. A VAT calculation that doesn't add up. A duplicate invoice nobody catches.
What We Do
Upload a document. Any format — PDF, scan, photograph, email attachment. In seconds, the system extracts every field: date, supplier name, tax ID (OIB), invoice number, line items with descriptions and quantities, unit prices, subtotals, VAT breakdown, total amount, payment terms, bank account.
But extraction is only half the job. Every output passes through our Pydantic validation layer — a deterministic firewall that checks what AI can't guarantee. Is the OIB exactly 11 digits? Does the sum of line items equal the subtotal? Does VAT at 25% match the declared amount?
How It Works
Ingest
Document arrives via upload, email forward, or API call.
OCR & Parse
AI reads the document, whether it's a clean PDF or a crumpled photo.
Extract
LLM identifies and extracts all relevant fields with contextual understanding.
Validate
Pydantic checks every field: format, mathematical consistency, cross-references.
Learn
When you correct an error, the system remembers. Next time, it gets it right.
Export
Structured output drops into your workflow. No copy-paste.
Technology
Concrete Example
A mid-sized accounting office processes 800 invoices per month. Each invoice takes 4 minutes manually — 53 hours/month on data entry. With Infera M, the same 800 invoices are processed in under 40 minutes, with higher accuracy.