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
Capture is genuinely strong: batch scanning with image clean-up, email archiving, bulk import and mobile intake are listed, and the AI recognises document type, applies the metadata template and extracts the fields — metadata is set at capture, which is exactly what I want to see. Natural-language smart fields pull invoice line items and email header data, with prebuilt templates for a dozen document types and handwriting recognition. What holds it back: no public information on a validation step or confidence scores, on duplicate detection, on XRechnung or ZUGFeRD e-invoice reading, or on where the AI processing runs. 1 2 5 6