AI-NATIVE DOCUMENT INFRASTRUCTURE

Turn documents into data your software can use.

StartOCR understands a document, structures the result, and keeps the confidence and source context your workflow needs.

DOCUMENT  →  DOCUMENT IR
{
  "status": "needs_review",
  "invoice": {
    "number": "INV-1048",
    "total": 1843.50
  },
  "confidence": 0.91
}
Try a document

FROM DOCUMENT TO USABLE DATA

Understand before you automate.

Document → Parse → Understand → Extract → Validate → Deliver.

REAL DOCUMENTS ARE MESSY

Evaluate the difficult files, not a perfect demo.

Use representative scans, multi-column PDFs, mixed text and images, rotated pages, tables, and long documents.

FIELD  total  ·  invoice.pdf
{
  "value": 1843.50,
  "confidence": 0.91,
  "needs_review": true
}

STRUCTURED OUTPUT

Ask for the fields you need.

Describe the outcome once, then reuse the same schema across your application and workflows.

POST /v1/extract
curl -X POST https://api.startocr.com/v1/extract
-H "Authorization: Bearer $STARTOCR_API_KEY"
-F file=@invoice.pdf \
-F schema=@invoice.json

RELIABILITY AND CONTROL

Keep every request observable.

Request IDs, async jobs, retries, webhooks, logs, usage, and field confidence make it easier to understand the production path.

START WITH ONE DIFFICULT DOCUMENT

Try the Playground. Get an API key.

Inspect a real result, define the output your system needs, then integrate the same request.