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Use case

Build an Expense Tracking App on the DocuParse API

Let users snap a receipt and get back merchant, date, total, tax, and line items as structured JSON — ready to store and categorize. Rule-based parsing reads every field, then an AI model checks the result and corrects what it finds wrong before you get it.
Try it on your document — no sign-up View the docs
97%

97% field-level accuracy

Tested on 500+ real receipts and invoices

Every result also carries confidence and needs_review.
How we test →

The workflow

1

Capture

A user uploads a receipt photo or PDF from your app.

2

Extract

Send it to the extraction endpoint and get named fields back.

3

Categorize

Use the merchant and line items to auto-categorize the expense.

4

Store

Save the structured record to your database with the confidence score.

Code

Submit the file, then fetch the JSON.

Every sample submits the file, then fetches the result until its status is completed or failed. On Starter and Pro, a webhook can deliver it instead.

# 1. Submit the document
curl -X POST https://docuparseapi.com/api/v1/extract \
  -H "Authorization: Bearer $DOCUPARSE_API_KEY" \
  -F "file=@document.pdf"
# → {"success": true, "document_id": "<id>", "status": "queued"}

# 2. Fetch the result (repeat until "status" is "completed" or "failed")
curl https://docuparseapi.com/api/v1/documents/<id> \
  -H "Authorization: Bearer $DOCUPARSE_API_KEY"

Fields you get

merchantdatecurrencysubtotaltaxtotalpayment_methodline_items[]confidence

Try it on your own document

Upload an invoice or receipt and see the structured JSON. No signup needed.

↑

Drop your receipt or invoice here, or click to choose

PDF · JPG · PNG · up to 10 pages · one document

Or try a sample: sample receipt · sample invoice

Sign up to use the API, bulk uploads and the spend dashboard.

How the extraction works
  1. Read — the document is converted to text with OCR (for images) or parsed directly (for digital PDFs).
  2. Parse — deterministic rules pull out each field and line item and normalize dates and amounts.
  3. Check — the result is scored for confidence: totals are reconciled (subtotal + tax = total), required fields are verified, and formats are validated.
  4. Review — an AI model then reviews every document and corrects the fields it finds wrong, looking hardest at the ones the rules were unsure of.

Every response includes a confidence score and a needs_review flag, so you always know which results to trust and which to double-check.

Try it on your own document.

20 documents a month free, with full API access. No credit card. Webhooks on Starter and Pro.

Try it on your document — no sign-up