PDFs, scans, and Word docs are one of the largest sources of manual work in any business. Today's AI (multimodal LLMs) can read almost any document and extract structured data. Here's how.
Thousands of PDFs per month (invoices, contracts, forms) processed manually
Classic OCR fails on poorly scanned or non-standard documents
Manual data entry into ERP/CRM after reading — major source of errors
Tedious manual validation of key fields (amounts, dates, IBANs)
List the 5-10 you process most: supplier invoice, customer invoice, contract, quote, receipt, declaration. For each, the 5-15 fields you always extract.
All documents land in one place: dedicated inbox, Drive/SharePoint folder, portal upload. That's the foundation of the auto flow.
Modern models (GPT-4 Vision, Claude, Gemini) read documents directly (PDF, JPG, scans), even with poor formatting. For standard documents, accuracy is 95-99%.
Total = sum of lines + VAT? IBAN valid? Due date after issue date? These checks happen by the system, not the human.
Only documents with confidence below 90% or failed validations reach a human. Everything else flows automatically into ERP/CRM.
For every extracted field: original document, extracted value, confidence score, who/what confirmed. Critical for tax audit or disputes.
Build custom if you process more than 1000 documents/month, have non-standard document types (industry-specific), or need complex validation (cross-document checks, history comparison). For low volume, generic solutions are enough.
For typical invoices from known suppliers, 99%+. For rare or poorly scanned documents, 90-95%. With training on your examples, we reach 97%+ even on difficult ones.
Partially. Printed text or standard handwritten fields (checked forms, amounts) are extractable with 85-95% accuracy. For long cursive text, accuracy drops. For critical handwritten fields, we recommend human validation.
For ERPs with APIs, direct integration. For old systems without APIs, we use RPA — a robot that 'enters' the extracted data like a human, but without errors.
Yes. For sensitive data (medical, legal, financial), we use AI models hosted on EU infrastructure or on-premise. Documents never leave your jurisdiction.
Typical: for a client processing 1000-2000 supplier invoices/month, 1-2 FTEs freed up. Automation cost recovers in 4-6 months.
30 minutes, no pitch — we’ll tell you honestly if it’s worth automating.
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