Capture, OCR & indexing
How this is scored
How documents get in and become findable: scanning and email intake, OCR, classification and metadata extraction, and whether incoming e-invoices (XRechnung, ZUGFeRD) are read as structured data rather than as pictures.
0 — Manual upload only; no OCR, no metadata beyond file name and folder.
3 — Upload, drag-and-drop and scan import with OCR mentioned, but indexing is manual and no word on email intake or e-invoice formats.
5 — Scanner, email and folder intake, full-text OCR, document types with metadata fields, and automatic extraction of common fields (date, sender, amount) documented.
8 — AI- or rule-based classification and field extraction with confidence and a validation step, XRechnung and ZUGFeRD read as structured data, mailbox and Microsoft 365 intake, and duplicate detection documented.
10 — Capture is engineered and shown: classification and extraction trainable per document type, validation queues, e-invoice validation against the standard, intake channels listed with their limits, and where AI processing runs (location, model provider) stated.
The Records Manager
Intake is broadly documented: paper via scanner, PDF, email and the Peppol e-invoice network, plus file-system import and camera capture, with OCR identifying recipients and booking-relevant fields such as invoice number, date, creditor and line items extracted automatically and matched against order data. ZUGFeRD and XRechnung are processed as structured data under the EN 16931 profiles, and an AI-assisted review step exists. We found no public information on duplicate detection or on the confidence of the classification and field extraction. 5 6 9 12