Extract Structured Data From Business Documents
Recognized text is not the same as structured data. AlQari turns documents into the specific fields your systems need — with confidence, validation, and JSON output — so people stop copying values out of PDFs by hand.
OCR text ≠ structured extraction
OCR converts an image into characters. You get the words on the page — but not which word is the invoice total, the vendor, or the due date. Extraction identifies the specific values you care about, attaches a confidence score to each, validates them against your rules, and returns clean JSON your systems can consume directly.
What you can extract
Key fields
Vendor, dates, identifiers, amounts, and other business fields, each with a confidence score.
Custom schema
Define the output structure you need so JSON matches the shape your systems expect.
Bounding boxes
Every extracted value can be traced back to its location on the page.
Validation rules
Automated checks (formats, required fields, simple math) run before data is trusted.
Human review
Low-confidence or failed-validation fields are routed to a person, not pushed through silently.
Line items where present
Tabular line items can be captured when the document contains them; results depend on layout and quality.
From document to validated JSON
- 1
OCR / layout
The document is read (Arabic + English) with layout preserved where supported.
- 2
Field extraction
Target fields are identified and pulled from the recognized text.
- 3
Confidence & validation
Each field gets a confidence score and is checked against your rules.
- 4
JSON / API output
Structured JSON is returned over the API; low-confidence fields can be flagged for review.
What extracted data looks like
A simplified, illustrative example — generic fields, not a real customer document. Each field carries its own confidence, and a review status indicates whether anything needs a human check.
Input
A scanned supplier invoice (PDF) with the vendor, invoice number, date, VAT number, and total scattered across the page in Arabic and English.
{
"documentType": "invoice",
"fields": {
"vendorName": { "value": "Example Trading Co.", "confidence": 0.97 },
"invoiceNumber": { "value": "INV-2024-0142", "confidence": 0.99 },
"invoiceDate": { "value": "2024-05-11", "confidence": 0.95 },
"vatNumber": { "value": "3•••••••••••003", "confidence": 0.93 },
"totalAmount": { "value": 14375.00, "currency": "SAR", "confidence": 0.96 }
},
"review": { "status": "passed", "flagged": [] }
}How AlQari compares to other platforms
See a transparent comparison of Arabic OCR, handwriting, structured extraction, validation, and workflow capabilities across leading document intelligence platforms.
View the Benchmark & ComparisonData extraction questions
What's the difference between OCR and extraction?
Can I define the output JSON schema?
How do I know which values to trust?
Do you extract tables and line items?
Does extraction work on Arabic documents?
How do I get the data out?
Stop copying data out of documents
See AlQari extract the fields you need — with confidence and validation — and return them as JSON.