CJK Invoice & Receipt OCR to JSON

Invoice OCR, receipt parser and document-to-JSON extractor built for Chinese and Japanese business documents. Upload a PDF, scan or phone photo of a Taiwan e-invoice (統一發票 / 電子發票), a Japanese qualified invoice (請求書 / 適格請求書 / インボイス), a receipt (收據 / 領収書) or a quotation (報價單 / 見積書) and get clean, validated JSON back.

Why use it

• Chinese / Japanese OCR that understands the document: Traditional Chinese, Japanese and English text, including scans and phone photos (deskew + upscaling).
• Built-in templates: Taiwan e-invoice, Japanese invoice, receipt, quotation. Or define your own fields with a JSON Schema or a simple field list such as {"seller": "string", "issueDate": "date", "items": ["string"]}.
• Validation you can trust: qty × unit price = amount, items sum to subtotal, subtotal + tax = total, Taiwan 5% VAT, Japanese 10% / 8% consumption tax, Taiwan 統一編號 checksum, Japanese registration number (T + 13 digits) checksum. Dates are normalised to ISO (民國 and 令和 years converted).
• Per-field confidence and a needsReview list so a human checks only what is uncertain.
• Smart model fallback: a fast vision LLM reads the document; when validation fails, a field is missing or confidence is low, a stronger model is tried automatically and the better result is kept. modelUsed and escalationReason tell you what happened.
• Works without an API key for built-in templates (OCR + rules engine). Optionally bring your own Gemini key.
• No data retention: files are processed in memory, never logged; uploaded inputs can be deleted after the run.

Quick start

Click Start with empty input to run a free demo on two synthetic invoices. Then add your own files:

{
  "fileUrls": ["https://example.com/invoice.pdf"],
  "template": "auto"
}

Supported files: PDF (text or scanned), PNG, JPEG, TIFF, WEBP.

Output

One dataset item per document:

{
  "source": "https://example.com/invoice.pdf",
  "template": "tw_einvoice",
  "engine": "llm+rules",
  "modelUsed": "gemini-flash-lite-latest",
  "data": {"invoiceNumber": "AB-12345678", "date": "2026-10-15", "sellerTaxId": "...", "totalAmount": 1575, "lineItems": [ ... ]},
  "confidence": {"invoiceNumber": 0.99, "totalAmount": 0.99},
  "overallConfidence": 0.99,
  "validation": {"passed": true, "checks": [ ... ]},
  "needsReview": [],
  "missingFields": []
}

Use cases

Accounts-payable automation, expense and receipt scanning, bookkeeping imports, procurement (quotation comparison), RAG / data pipelines that need structured data from Chinese or Japanese PDFs.

Tips

• For messy phone photos and custom schemas, the LLM engine gives the best accuracy.
• Check needsReview and validation.passed before posting data to your accounting system.

Keywords

invoice OCR, receipt parser, document to JSON, Chinese OCR, Japanese OCR, Taiwan e-invoice, 統一發票, Japanese invoice, 請求書, インボイス, 領収書, 見積書, PDF to JSON, AI document extraction