Document Tools
OCR PDF to Structured JSON Bridge
Extract the PDF text layer with geometry (lines by y-position, tables by column gaps, headings by font size, colon key-value pairs), then fill a user-supplied JSON Schema field by field — labels matched by normalized keys, values coerced to declared types and validated with ajv.
Quick start
Call this tool from your code in three languages.
# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/ocr-pdf-to-structured-json-bridge' \
-H 'Content-Type: application/json' \
-d '{"filename":"pdfFile.ext","contentType":"application/octet-stream","size":12345}'
# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
--data-binary @/path/to/file.ext
# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/en/api/tools/ocr-pdf-to-structured-json-bridge' \
-F 'pdfFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
-F 'schemaInput={
"type": "object",
"properties": {
"invoice_number": { "type": "string" },
"invoice_date": { "type": "string", "format": "date" },
"customer": { "type": "string" },
"currency": { "type": "string", "enum": ["USD", "EUR"] },
"total": { "type": "number" }
},
"required": ["invoice_number", "total"]
}' \
-F 'numberStyle=auto'