extract-document-data

Extract Document Data

Extract structured JSON from documents with per-value grounding: every extracted value cites where it came from (page number, confidence), and values that aren't clearly present are reported in not_found rather than hallucinated. Uses the Stipple API (free anonymous tier).

When to use

• Parsing payslips, invoices, bank statements, receipts, or contracts
• Converting unstructured documents to JSON for downstream systems
• Any extraction where hallucinated values are worse than missing values (lending, accounting, compliance)

Instructions

1. Get the document. URL or local file path (PDF, PNG, JPEG, DOCX).

1. Choose the extraction mode:

• Ad-hoc fields — tell the API exactly which fields you want:

``bash curl -X POST https://www.stipple.sh/v1/extract \ -F "file=@payslip.pdf" \ -F 'fields=[{"name":"employer_name"},{"name":"net_pay"},{"name":"pay_date"}]' \ -H "Authorization: Bearer $STIPPLE_API_KEY" ``

• Template — use a built-in schema: payslip, tax_invoice, bank_statement, receipt, contract
• Schema-free — omit fields and let the model extract what it finds

1. Interpret the response.

```json { "mode": "schema_free", "document_type": "payslip", "pages_read": 1, "fields": { "employer_name": {"value": "Acme Cleaning Pty Ltd", "c