Send a receipt image or PDF to one REST endpoint and get back structured JSON: vendor, date, payment method, line items, sales tax, and total. Bearer-token auth, no template setup, and the same AI engine that powers the web app. Test it in the browser below, then wire it into your product.
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Teams that need receipt data inside their own app, expense tool, or accounting integration usually underestimate what it takes to read a real receipt reliably. The result is months of work to get something a dedicated API already does.
Tesseract and similar libraries hand you a wall of raw text. You still have to write and maintain the parsing logic that decides which number is the total, which is tax, and which line is an item. That logic breaks on every new merchant.
There is no standard receipt format. A regex or template that works for one chain fails on the next. Keeping field extraction accurate across thousands of merchants is a full-time job your team probably should not own.
Faded thermal paper, multi-page totals, foreign characters, and phone photos shot at an angle are where homegrown extraction quietly fails. Each fix is another sprint that is not shipping your actual product.
Many vendors hide per-call costs behind "contact sales," which makes it hard for a technical lead to forecast spend at volume. You want a clear endpoint, a clear response, and a clear price.
The ReceiptOCR API wraps the same AI extraction engine behind the web app in a simple REST interface. You upload a receipt, poll for the result, and receive validated JSON your code can use directly.
Every call returns structured JSON with named fields for vendor, date, payment method, subtotal, sales tax, total, and an array of line items. No screen-scraping, no parsing raw OCR text on your end.
Authenticate with a single Bearer token in the Authorization header. Generate a key, drop it into your request, and you are calling the API in minutes with standard HTTP.
The model reads any receipt layout from any US merchant without per-vendor configuration. You do not build or maintain parsing rules, and accuracy holds as new merchants appear.
Post a JPG, PNG, or PDF to the upload endpoint. Faded thermal scans, emailed PDF confirmations, and smartphone photos all return the same structured response.
Get individual line items with descriptions, quantities, and prices in the response, not just the grand total. That is what makes the data usable for categorization and reconciliation.
Documented rate limits and a clear request flow mean you can plan for production load instead of guessing. Scale receipt processing inside your app without standing up your own OCR stack.
A straightforward upload-then-retrieve flow you can integrate in an afternoon.
POST your receipt image or PDF to the upload endpoint with your Bearer token. The API accepts JPG, PNG, and PDF files and queues the document for extraction.
Tip: Use the /api/documents/types endpoint to confirm supported document types programmatically.
Call the extract endpoint for the document. The AI engine reads the vendor, date, payment method, line items, subtotal, sales tax, and total from whatever layout the merchant used.
Fetch the extraction result and receive clean JSON your application can store, validate, or push into QuickBooks, Xero, or your own database. No manual review step required.
Built for US developers and product teams who need receipt data extraction inside their own software, without owning an OCR pipeline.
Add receipt capture to an expense, accounting, or fintech product without building extraction from scratch.
Wire receipt OCR into Zapier, Make, or a custom backend so receipts flow into your books automatically.
Feed employee and vendor receipts straight into your AP or ERP system through a single API call.
Let users snap a receipt in your mobile app and return categorized data in seconds via the API.
A receipt OCR API is a web service that takes a receipt image or PDF and returns the extracted fields as structured data, usually JSON. Instead of running optical character recognition and writing your own parser, you send the file to an endpoint and get back named values for vendor, date, sales tax, total, and line items. The API handles the hard part, turning pixels into accounting-ready fields, so your application just consumes the result.
Open-source OCR returns raw text, which means you still own the logic that decides which token is the total and which line is an item. That parsing layer is where most homegrown projects stall, because receipt layouts vary by merchant and change without notice. A dedicated receipt data extraction API gives you a maintained model that reads any layout, so you ship the feature in days and never chase a vendor-specific format again.
Integration follows three calls. You POST the receipt to the upload endpoint with a Bearer token, trigger extraction on that document, then retrieve the structured JSON result. The response includes the merchant, transaction date, payment method, subtotal, itemized lines with quantities and prices, sales tax, and total. Full request and response examples in cURL and JSON live in the API documentation.
Real input is messy. The API accepts JPG, PNG, and PDF, and the same AI engine reads faded thermal paper, emailed order confirmations, and phone photos shot at an angle. Because extraction is model-based rather than template-based, you get consistent JSON across merchants without writing conditional logic for each receipt style your users upload.
Once you have structured fields, the integration is yours to define. Store the JSON in your database, map it to a QuickBooks or Xero import, or push it into an AP workflow. Every receipt returns the same field structure, so your downstream mapping is written once and reused. If your team only needs a spreadsheet rather than an API, the receipt OCR software and receipt to Excel converter run the same engine through the browser.
Most developers evaluating this category end up looking at the same short list, and the deciding factor is rarely extraction quality on clean documents, where everyone performs well. It is the commercial shape of the product. The Veryfi alternative comparison covers the $500 monthly minimum on its paid API tier, and the Nanonets alternative comparison covers prepaid credits metered per processing block. Before you pick, it is worth understanding how accurate receipt OCR really is, and why a headline accuracy percentage tells you almost nothing without knowing whether it was measured per character or per field.
A receipt OCR API is a web service that accepts a receipt image or PDF and returns the extracted data as structured JSON. It reads the vendor, date, line items, sales tax, and total for you, so your application consumes ready-to-use fields instead of running OCR and writing parsing logic yourself.
The API returns clean JSON with named fields for merchant, transaction date, payment method, subtotal, sales tax, and total, plus an array of line items with descriptions, quantities, and prices. Your code can store or map that response directly without parsing raw text.
Authentication uses a Bearer token passed in the Authorization header of each request. You generate an API key, include it in standard HTTP calls to the upload and extract endpoints, and you are integrated. Full cURL examples are in the API documentation.
The API reaches 99%+ accuracy on standard fields like vendor, date, total, and sales tax, using the same AI engine as the web app. Because it is model-based rather than template-based, accuracy holds across merchant layouts and on faded thermal or photographed receipts.
Yes. The upload endpoint accepts JPG, PNG, and PDF files. The same extraction engine handles scanned paper, emailed PDF confirmations, and smartphone photos, returning the same structured JSON regardless of the input format.
Yes. The response includes an array of individual line items with descriptions, quantities, and prices, alongside the subtotal, sales tax, and grand total. That detail is what makes the output usable for expense categorization and reconciliation in your app.
Yes. The API publishes documented rate limits so you can plan for production load. The request flow and current limits are described in the API documentation, which lets you size your integration before going live.
Yes. That is the primary use case. Product teams, automation engineers, and finance tech teams call the REST endpoints to add receipt capture to expense tools, accounting platforms, and AP pipelines without building or maintaining their own OCR stack.
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