Solution · Operations & back office

Documents that read themselves.

  • Pilot in 2–4 weeks

Transport documents, delivery notes, CMRs, PODs and invoices get detected, extracted and prepared for review. Your team checks and approves.

Sound familiar?

  • Documents come as PDF, scan, photo or mail attachment — always different
  • Staff type positions, numbers and dates manually
  • Error rate 3–8%, every correction costs time
  • Delayed processing blocks approvals and billing

Fits well when …

  • Logistics, forwarding and trade companies with high document volume
  • Back-office teams that still type a lot
  • Companies with API-addressable ERP/TMS

How we solve it

Automatic extraction with a clear review view. Human decides on exceptions.

1. Detect document

The system detects the document type (delivery note, CMR, POD, invoice) and routes it to the right process.

2. Extract data

All relevant fields (positions, quantities, numbers, dates) are read and structured.

3. Flag errors

Unsure fields and discrepancies (e.g. quantity mismatches) get colour-coded.

4. Prepare ERP export

The record is shaped so it goes into ERP/TMS with one click after approval.

Before · After

Before

  • 4 staff, 1,200 documents/day
  • Handling: 3–5 minutes per document
  • Error rate 5–8%
  • Manual typing and copying

After

  • Handling: < 30 seconds per document
  • Error rate < 1%
  • System handles extraction
  • Team only checks exceptions

Example numbers

This is what relief looks like.

Volume

~1,200 docs/day

Handling time

-85%

80h → 12h manual

Savings

~€35k / month

4 people in back office

Indicative figures from pilots and comparable projects. Actual numbers depend on your setup.

Data protection and setup

GDPR-compliant, optional local processing. Audit trail for every extraction. No data leaves your systems without clear approval in the architecture.

How many hours go into document typing at your company every day?

The bottleneck check shows which documents are worth it — and which aren't.