Invoice and Text to JSON Extraction API

API ID 14523

Turn invoices, receipts and unstructured text into structured JSON with confidence scores.

API Documentation

Endpoints

Request
Invoice or receipt (PDF, PNG/JPEG/WebP image, or plain text) to structured JSON with a fixed schema: vendor (name, address, VAT ID, email, phone, IBAN), customer, invoice number, order number, issue/due date, currency (ISO 4217), subtotal, VAT total, total, amount due, VAT breakdown and line items. Every field has value, the verbatim source quote and a confidence score (0-1: quote found in the document, value matches quote, totals add up). Arithmetic checks included. Runs on Cloudflare Workers AI only (PDF text layer via toMarkdown, OCR for images); documents are not stored. Scanned PDFs without a text layer: send page images. POST JSON {url} or {file_base64, mime_type} or {text}, or POST the raw file (Content-Type application/pdf or image/*); GET ?url= or ?text= also works. When to use: Use invoice-json for invoices and receipts (fixed accounting schema, quotes, arithmetic checks). Use extract-json for any other short text with your own JSON schema. Use page-rag to turn a web page into Markdown for retrieval.
Endpoint ID: 37076
GET https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37076/invoice+to+json
INPUT PARAMETERS

Invoice to JSON — Endpoint Features

Object Description
url Optional public http(s) URL of a PDF, PNG, JPEG or WebP invoice/receipt (max 8 MB)
text Optional invoice text instead of a file (max 40,000 chars)

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

url
text
API EXAMPLE RESPONSE
JSON
{
    "document_type": {
        "value": "invoice",
        "quote": "Invoice INV/2023/03/0008",
        "confidence": 0.9
    },
    "vendor": {
        "name": {
            "value": "Global Wholesaler",
            "quote": "Global Wholesaler",
            "confidence": 0.95
        },
        "address": {
            "value": "Azure Interior 4557 De Silva St Fremont CA 94538 United States",
            "quote": "Azure Interior 4557 De Silva St Fremont CA 94538 United States",
            "confidence": 0.95
        },
        "vat_id": {
            "value": null,
            "quote": null,
            "confidence": null
        },
        "email": {
            "value": "[email protected]",
            "quote": "[email protected]",
            "confidence": 0.95
        },
        "phone": {
            "value": "(870)-931-0505",
            "quote": "(870)-931-0505",
            "confidence": 0.95
        },
        "iban": {
            "value": "US1234567890",
            "quote": "US1234567890",
            "confidence": 0.95
        }
    },
    "customer": {
        "name": {
            "value": "YourCompany",
            "quote": "YourCompany, Mitchell Admin",
            "confidence": 0.95
        },
        "address": {
            "value": "215 Vine St Scranton PA 18503 United States",
            "quote": "215 Vine St Scranton PA 18503 United States",
            "confidence": 0.95
        },
        "vat_id": {
            "value": null,
            "quote": null,
            "confidence": null
        }
    },
    "invoice_number": {
        "value": "INV/2023/03/0008",
        "quote": "Invoice INV/2023/03/0008",
        "confidence": 0.95
    },
    "order_number": {
        "value": "CUSTREF123",
        "quote": "Reference:CUSTREF123",
        "confidence": 0.95
    },
    "issue_date": {
        "value": "2023-03-20",
        "quote": "03/20/2023",
        "confidence": 0.9
    },
    "due_date": {
        "value": "2023-04-04",
        "quote": "04/04/2023",
        "confidence": 0.9
    },
    "currency": {
        "value": "USD",
        "quote": "$ 112.00",
        "confidence": 0.9
    },
    "payment_terms": {
        "value": "15 Days",
        "quote": "Payment terms: 15 Days",
        "confidence": 0.95
    },
    "totals": {
        "subtotal": {
            "value": 262.9,
            "quote": "Subtotal $ 262.90",
            "confidence": 0.98
        },
        "vat_total": {
            "value": 16.94,
            "quote": "Tax 15% on $ 112.90 $ 16.94",
            "confidence": 0.98
        },
        "total": {
            "value": 279.84,
            "quote": "Total $ 279.84",
            "confidence": 0.98
        },
        "amount_due": {
            "value": null,
            "quote": null,
            "confidence": null
        }
    },
    "vat_breakdown": [
        {
            "rate": 15,
            "base": 112.9,
            "amount": 16.94,
            "quote": "$ 16.94",
            "confidence": 0.85
        }
    ],
    "line_items": [
        {
            "description": "Beeswax XL",
            "quantity": 1,
            "unit_price": 42,
            "amount": 42,
            "vat_rate": 15,
            "quote": "[17589684] Beeswax XL Acme beeswax 1.00 kg 42.00 0.00 15.00% $ 42.00",
            "confidence": 0.85
        },
        {
            "description": "Office Chair",
            "quantity": 1,
            "unit_price": 70,
            "amount": 70,
            "vat_rate": 15,
            "quote": "[FURN_7777] Office Chair 1.00 Units 70.00 0.00 15.00% $ 70.00",
            "confidence": 0.85
        },
        {
            "description": "Olive Oil",
            "quantity": 1,
            "unit_price": 1,
            "amount": 0.9,
            "vat_rate": 15,
            "quote": "*987123* Olive Oil 1.00 L 1.00 10.00 15.00% $ 0.90",
            "confidence": 0.85
        },
        {
            "description": "Luxury Truffles",
            "quantity": 15,
            "unit_price": 10,
            "amount": 150,
            "vat_rate": null,
            "quote": "[LUX_TRF] Luxury Truffles 15.00 g 10.00 0.00 $ 150.00",
            "confidence": 0.85
        }
    ],
    "checks": {
        "subtotal_plus_vat_equals_total": true,
        "line_items_sum_equals_subtotal_or_total": true,
        "vat_breakdown_sum_equals_vat_total": true,
        "due_date_not_before_issue_date": true
    },
    "overall_confidence": 0.94,
    "missing": [
        "vendor_vat_id",
        "customer_vat_id",
        "amount_due"
    ],
    "pages": 1,
    "billed_usd": 0.0075,
    "input": "pdf",
    "text_chars": 1036,
    "model": "@cf/mistralai/mistral-small-3.1-24b-instruct",
    "timing_ms": {
        "pdf_text_ms": 826,
        "extract_ms": 14828,
        "total": 15654
    },
    "confidence_method": "Per field: 0.6 if the quote is found verbatim in the document text (+0.3 if the value matches the quote; 0.35 base if the quote is not verbatim), then +0.08/-0.15 from the arithmetic checks for totals. Values with confidence < 0.6 should be reviewed.",
    "limits": "LLM extraction can misread layouts; check important values (quotes make that quick). Scanned PDFs need image input. Documents are not stored.",
    "sources": [
        {
            "name": "Cloudflare Workers AI: toMarkdown (PDF text layer), Mistral Small 3.1 24B (OCR of images + field extraction; fallback Llama 3.3 70B / Llama 4 Scout / Gemma 3 12B)",
            "url": "https://developers.cloudflare.com/workers-ai/",
            "note": "Documents are processed in memory and not stored or logged. No third-party LLM API."
        }
    ]
}
Invoice to JSON — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37076/invoice+to+json?url=https://raw.githubusercontent.com/invoice-x/invoice2data/master/tests/compare/AzureInterior.pdf' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
Invoice or receipt (PDF, PNG/JPEG/WebP image, or plain text) to structured JSON with a fixed schema: vendor (name, address, VAT ID, email, phone, IBAN), customer, invoice number, order number, issue/due date, currency (ISO 4217), subtotal, VAT total, total, amount due, VAT breakdown and line items. Every field has value, the verbatim source quote and a confidence score (0-1: quote found in the document, value matches quote, totals add up). Arithmetic checks included. Runs on Cloudflare Workers AI only (PDF text layer via toMarkdown, OCR for images); documents are not stored. Scanned PDFs without a text layer: send page images. POST JSON {url} or {file_base64, mime_type} or {text}, or POST the raw file (Content-Type application/pdf or image/*); GET ?url= or ?text= also works. When to use: Use invoice-json for invoices and receipts (fixed accounting schema, quotes, arithmetic checks). Use extract-json for any other short text with your own JSON schema. Use page-rag to turn a web page into Markdown for retrieval.
Endpoint ID: 37077
POST https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37077/invoice+to+json+post
INPUT PARAMETERS

Invoice to JSON POST — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{
    "document_type": {
        "value": "invoice",
        "quote": "Invoice INV/2023/03/0008",
        "confidence": 0.9
    },
    "vendor": {
        "name": {
            "value": "Global Wholesaler",
            "quote": "Global Wholesaler",
            "confidence": 0.95
        },
        "address": {
            "value": "Azure Interior 4557 De Silva St Fremont CA 94538 United States",
            "quote": "Azure Interior 4557 De Silva St Fremont CA 94538 United States",
            "confidence": 0.95
        },
        "vat_id": {
            "value": null,
            "quote": null,
            "confidence": null
        },
        "email": {
            "value": "[email protected]",
            "quote": "[email protected]",
            "confidence": 0.95
        },
        "phone": {
            "value": "(870)-931-0505",
            "quote": "(870)-931-0505",
            "confidence": 0.95
        },
        "iban": {
            "value": "US1234567890",
            "quote": "US1234567890",
            "confidence": 0.95
        }
    },
    "customer": {
        "name": {
            "value": "YourCompany",
            "quote": "YourCompany, Mitchell Admin",
            "confidence": 0.95
        },
        "address": {
            "value": "215 Vine St Scranton PA 18503 United States",
            "quote": "215 Vine St Scranton PA 18503 United States",
            "confidence": 0.95
        },
        "vat_id": {
            "value": null,
            "quote": null,
            "confidence": null
        }
    },
    "invoice_number": {
        "value": "INV/2023/03/0008",
        "quote": "Invoice INV/2023/03/0008",
        "confidence": 0.95
    },
    "order_number": {
        "value": "CUSTREF123",
        "quote": "Reference:CUSTREF123",
        "confidence": 0.95
    },
    "issue_date": {
        "value": "2023-03-20",
        "quote": "03/20/2023",
        "confidence": 0.9
    },
    "due_date": {
        "value": "2023-04-04",
        "quote": "04/04/2023",
        "confidence": 0.9
    },
    "currency": {
        "value": "USD",
        "quote": "$ 112.00",
        "confidence": 0.9
    },
    "payment_terms": {
        "value": "15 Days",
        "quote": "Payment terms: 15 Days",
        "confidence": 0.95
    },
    "totals": {
        "subtotal": {
            "value": 262.9,
            "quote": "$ 262.90",
            "confidence": 0.98
        },
        "vat_total": {
            "value": 16.94,
            "quote": "$ 16.94",
            "confidence": 0.98
        },
        "total": {
            "value": 279.84,
            "quote": "$ 279.84",
            "confidence": 0.98
        },
        "amount_due": {
            "value": null,
            "quote": null,
            "confidence": null
        }
    },
    "vat_breakdown": [
        {
            "rate": 15,
            "base": 112.9,
            "amount": 16.94,
            "quote": "$ 16.94",
            "confidence": 0.85
        }
    ],
    "line_items": [
        {
            "description": "Beeswax XL",
            "quantity": 1,
            "unit_price": 42,
            "amount": 42,
            "vat_rate": 15,
            "quote": "[17589684] Beeswax XL Acme beeswax 1.00 kg 42.00 0.00 15.00% $ 42.00",
            "confidence": 0.85
        },
        {
            "description": "Office Chair",
            "quantity": 1,
            "unit_price": 70,
            "amount": 70,
            "vat_rate": 15,
            "quote": "[FURN_7777] Office Chair 1.00 Units 70.00 0.00 15.00% $ 70.00",
            "confidence": 0.85
        },
        {
            "description": "Olive Oil",
            "quantity": 1,
            "unit_price": 1,
            "amount": 0.9,
            "vat_rate": 15,
            "quote": "*987123* Olive Oil 1.00 L 1.00 10.00 15.00% $ 0.90",
            "confidence": 0.85
        },
        {
            "description": "Luxury Truffles",
            "quantity": 15,
            "unit_price": 10,
            "amount": 150,
            "vat_rate": null,
            "quote": "[LUX_TRF] Luxury Truffles 15.00 g 10.00 0.00 $ 150.00",
            "confidence": 0.85
        }
    ],
    "checks": {
        "subtotal_plus_vat_equals_total": true,
        "line_items_sum_equals_subtotal_or_total": true,
        "vat_breakdown_sum_equals_vat_total": true,
        "due_date_not_before_issue_date": true
    },
    "overall_confidence": 0.94,
    "missing": [
        "vendor_vat_id",
        "customer_vat_id",
        "amount_due"
    ],
    "pages": 1,
    "billed_usd": 0.0075,
    "input": "pdf",
    "text_chars": 1036,
    "model": "@cf/mistralai/mistral-small-3.1-24b-instruct",
    "timing_ms": {
        "pdf_text_ms": 719,
        "extract_ms": 17579,
        "total": 18298
    },
    "confidence_method": "Per field: 0.6 if the quote is found verbatim in the document text (+0.3 if the value matches the quote; 0.35 base if the quote is not verbatim), then +0.08/-0.15 from the arithmetic checks for totals. Values with confidence < 0.6 should be reviewed.",
    "limits": "LLM extraction can misread layouts; check important values (quotes make that quick). Scanned PDFs need image input. Documents are not stored.",
    "sources": [
        {
            "name": "Cloudflare Workers AI: toMarkdown (PDF text layer), Mistral Small 3.1 24B (OCR of images + field extraction; fallback Llama 3.3 70B / Llama 4 Scout / Gemma 3 12B)",
            "url": "https://developers.cloudflare.com/workers-ai/",
            "note": "Documents are processed in memory and not stored or logged. No third-party LLM API."
        }
    ]
}
Invoice to JSON POST — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37077/invoice+to+json+post' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{"url":"https://raw.githubusercontent.com/invoice-x/invoice2data/master/tests/compare/AzureInterior.pdf"}'

    
Request
Messy text + JSON Schema in, clean JSON out. Uses a small LLM (Cloudflare Workers AI, Llama 3.1 8B, JSON mode) when available, else a deterministic key:value/regex extractor; the result is type-checked against your schema and missing fields are null. Limits: text
Endpoint ID: 37078
GET https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37078/text+to+json
INPUT PARAMETERS

Text to JSON — Endpoint Features

Object Description
text Required input text, max 6000 chars
schema Required JSON Schema (type object with properties) as a JSON string

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

text
schema
API EXAMPLE RESPONSE
JSON
{
    "data": {
        "order_id": "4471",
        "company": "ACME GmbH",
        "total": 1299,
        "currency": "EUR",
        "due_date": "2026-11-30",
        "email": "[email protected]"
    },
    "method": "workers-ai",
    "model": "@cf/meta/llama-3.1-8b-instruct-fp8-fast",
    "missing": [],
    "not_verbatim_in_text": [],
    "limits": "Small-model / heuristic extraction; check important values. Text is not stored.",
    "sources": [
        {
            "name": "Cloudflare Workers AI (Llama 3.1 8B fp8-fast, fallback Llama 3.3 70B / Mistral Small 3.1, JSON mode)",
            "url": "https://developers.cloudflare.com/workers-ai/"
        }
    ]
}
Text to JSON — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37078/text+to+json?text=Order #4471 from ACME GmbH, total EUR 1.299,00, due 2026-11-30, contact [email protected]&schema={"type":"object","properties":{"order_id":{"type":"string"},"company":{"type":"string"},"total":{"type":"number"},"currency":{"type":"string"},"due_date":{"type":"string","format":"date"},"email":{"type":"string","format":"email"}}}' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request
Messy text + JSON Schema in, clean JSON out. Uses a small LLM (Cloudflare Workers AI, Llama 3.1 8B, JSON mode) when available, else a deterministic key:value/regex extractor; the result is type-checked against your schema and missing fields are null. Limits: text
Endpoint ID: 37079
POST https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37079/text+to+json+post
INPUT PARAMETERS

Text to JSON POST — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{
    "data": {
        "order_id": "4471",
        "total": 1299
    },
    "method": "workers-ai",
    "model": "@cf/meta/llama-3.1-8b-instruct-fp8-fast",
    "missing": [],
    "not_verbatim_in_text": [],
    "limits": "Small-model / heuristic extraction; check important values. Text is not stored.",
    "sources": [
        {
            "name": "Cloudflare Workers AI (Llama 3.1 8B fp8-fast, fallback Llama 3.3 70B / Mistral Small 3.1, JSON mode)",
            "url": "https://developers.cloudflare.com/workers-ai/"
        }
    ]
}
Text to JSON POST — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/14523/invoice+and+text+to+json+extraction+api/37079/text+to+json+post' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{"text":"Order ID: 4471, Total: EUR 1.299,00","schema":{"type":"object","properties":{"order_id":{"type":"string"},"total":{"type":"number"}}}}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Invoice and Text to JSON Extraction API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.

Starts at
$10,000/Year


  • Custom Volume
  • Custom Rate Limit
  • Specialized Customer Support
  • Real-Time API Monitoring

Overview

Turn invoices, receipts and unstructured text into structured JSON with confidence scores.

Invoice and Text to JSON Extraction API FAQs

The Invoice to JSON endpoints return structured JSON data from invoices and receipts, including vendor details, customer information, invoice numbers, and financial totals. The Text to JSON endpoints return clean JSON based on messy text input, structured according to a user-defined schema.

Key fields in the Invoice to JSON response include vendor name, address, VAT ID, email, phone, invoice number, issue date, currency, subtotal, VAT total, and line items. For Text to JSON, key fields depend on the provided schema, such as order ID, total, and due date.

The returned data is in JSON format, structured with key-value pairs. For invoices, it follows a fixed schema with nested objects for vendor and customer details. Text to JSON responses are structured based on the user-defined schema, ensuring type consistency.

The Invoice to JSON endpoints provide detailed invoice and receipt information, including vendor and customer data, financial totals, and line items. The Text to JSON endpoints extract relevant data from unstructured text based on a specified schema.

Users can send parameters such as {url}, {file_base64, mime_type}, or {text} for the Invoice to JSON endpoints. For Text to JSON, users provide messy text and a JSON schema. GET requests can also use ?url= or ?text= parameters.

The response data is organized into structured JSON objects. Each key field contains a value, a verbatim quote from the source, and a confidence score. This organization allows users to easily access and interpret the extracted information.

Data accuracy is maintained through confidence scores for each extracted field, indicating the reliability of the information. Arithmetic checks ensure that totals match, and the use of advanced AI models enhances extraction quality.

Typical use cases include automating invoice processing, extracting key information from receipts for accounting, and converting unstructured text into structured data for analysis. Users can streamline data entry and improve accuracy in financial records.

General FAQs

To obtain your API key, first sign in to your account and navigate to the API you want to use. From the API's Pricing section, choose a plan and complete the subscription process. Once subscribed, return to the API page and you will see your API Access Key displayed at the top of the documentation page. You can use this key to authenticate your requests.

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