Paper in.
Fields out.
Warranty cards, invoices, forms, meter readings, inspection sheets. Define the fields you need and Steve extracts them from photos or scans, with a confidence score per field and a review queue for the doubtful ones.
Steve{ "document_type": "Warranty registration", "serial_number": "SN-88213-Q", "purchase_date": "2026-08-30", "dealer": "Nordic Home", "confidence": 0.97, "needs_review": false}The evidence and your rules.
- Photos or scans submitted through the mobile app or the API
- The list of fields you need, and their types
- Optional validation rules, such as totals that must add up
Fields, a verdict, and the proof.
- Structured fields with a confidence score each, delivered by API or webhook
- A verdict against your rules: approved, flagged for review, or blocked
- The evidence and the reason, side by side, in a review queue your team can act on
Rules you would write on a whiteboard. Applied to every submission.
Field-level confidence
Every extracted value carries a confidence score. Set a threshold and only low-confidence documents reach a person.
Validation rules
Relations and date windows catch impossible values before they hit your database.
Duplicate detection
The same document submitted twice is recognised, visually and by its identity fields.
From capture to decision.
Define fields
Name the fields and types. No templates, no zones to draw.
Submit
Send documents in sessions through the API, with idempotent client ids.
Extract
Steve returns structured JSON with confidence and any rule violations.
Consume
Webhooks notify your systems the moment a document is ready.
Industries using this today.
Is this just OCR?
No. OCR gives you characters. Steve gives you the fields you asked for, typed, validated, and deduplicated, from documents it has never seen before.
Same engine. Different evidence.
Let’s run it
on your evidence.
Bring a handful of real image samples and the rules you apply today. We will show you what Steve returns.
Book a demo 30 minutes. Your use case. Real possibilities.