Stijn AI
Data

Document Extractor

Pulls structured fields out of invoices, contracts and forms.

Document Extractor turns a PDF into a row. Define the fields you want once, point it at invoices, purchase orders, contracts, shipping documents or application forms, and get back clean typed JSON with a confidence score per field.

Schema first

You describe the fields you want and their types. The agent returns exactly that shape every time, or explicitly nulls a field it could not find. It never invents a plausible value to fill a gap, which is the failure mode that makes most extraction tools unusable in an accounts payable workflow.

Layout independence

It reads meaning rather than position, so it handles the thirty different invoice layouts your suppliers use without a template per supplier. This is the practical difference between a system you can roll out this quarter and one that needs a configuration project first.

Per-field confidence

Each extracted field carries its own confidence. In production this matters enormously: you can auto-approve documents where every field is above 0.95 and route only the rest to a human. Most customers find that clears 80% of their volume without review.

What it can do

  • Extract to a schema you define
  • Handle arbitrary layouts without per-vendor templates
  • Return per-field confidence scores
  • Null a field rather than guess at it
  • Normalise dates, currencies and numbers
  • Read line-item tables into arrays
  • Process scanned documents through OCR
  • Flag documents that do not match the expected type

Inputs and outputs

It takes

  • Document (PDF, image, DOCX)
  • Field schema
  • Expected document type (optional)

It returns

{ "fields{}": ... "confidence{}": ... "line_items[]": ... "document_type": ... "warnings[]": ... }

Fit

Good for

  • Accounts payable automation
  • Contract data migration
  • KYC and onboarding forms
  • Logistics paperwork

Not for

  • Handwriting-heavy documents
  • Legal interpretation of contract terms
  • Signature verification