Google Cloud Document AI is a strong document platform, and its Invoice and Expense parsers read invoices and receipts accurately. Like AWS Textract, it is a developer API: you need a Google Cloud project, and the output is JSON, so getting the data into Excel is code you write. ReceiptOCR does the same receipt and invoice extraction as a browser tool. Upload a document, review every field, and export Excel, CSV, or a QuickBooks-ready file, with a REST API available when you want it. If you are building document processing into an application, Document AI is a serious option. If you just want the fields in a spreadsheet, upload one below.
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Document AI has dedicated Invoice and Expense parsers that extract the right fields. The friction is the same as with any cloud OCR API: it is built to be called from code inside a Google Cloud project, not opened in a browser by the person who has the receipts.
Using Document AI means a GCP project, enabled APIs, credentials, and a processor you provision. That is a normal afternoon for a developer and a non-starter for a bookkeeper who just wants receipts in a sheet.
The Invoice and Expense parsers return structured JSON. There is no CSV or Excel download and no QuickBooks file, so someone writes code to turn the entities into rows before it is usable in accounting.
Document AI is headless. There is no screen to check the extracted total against the document before it flows on, so validation is logic you build rather than a glance you take.
The specialized parsers do not have a permanent free allotment. Google offers general new-customer credit, but Document AI itself meters from the start, at $10 per 1,000 pages for the Invoice and Expense parsers.
ReceiptOCR reads receipts and invoices with AI, shows you every field, and exports a spreadsheet. No Google Cloud project, no credentials, no parsing code, and a REST API for when you do want to integrate.
Drag in a receipt, an invoice, or a batch. No GCP console, no processor to provision, no service account key to manage.
Download the spreadsheet or a QuickBooks-ready file directly. Developers can still take JSON over the API, so nobody has to write a parser to get rows.
Every field is on screen and editable, so a misread total is caught before it becomes a row rather than after it hits your books.
Vendor, date, tax, subtotal, and total, plus each line item, the same fields the Invoice and Expense parsers return, delivered as a sheet.
US dollars, pay-as-you-go, no per-seat fee, and no cloud metering to monitor. Start the same session you sign up.
The API returns the same fields as JSON without a Google Cloud project and processor standing behind every call.
What takes a GCP project and parsing code with Document AI takes three clicks here.
A single receipt or a month of invoices, PDFs, scans, and photos together, with no processor to configure first.
Tip: Mix vendors freely. There is no per-layout processor to pick, unlike choosing between the Invoice and Expense parsers.
Review vendor, date, tax, total, and every line item on screen, and correct anything flagged before it becomes a row.
Download Excel, CSV, or a QuickBooks-ready file, or call the REST API for the same fields as JSON.
Document AI is built for engineers embedding extraction into software. These are the people who need the same output without the project.
Client receipts into a ledger, not a Google Cloud processor to provision and bill.
Vendor invoices into rows that post to accounting, with no engineer between the bill and the export.
A few hundred documents a month and no developer to stand up a GCP pipeline and maintain it.
An endpoint that returns clean fields as JSON without enabling APIs, minting credentials, and provisioning a processor.
Last updated July 2026.
Google Cloud Document AI is a capable platform, and its specialized parsers for invoices and receipts are accurate. This page is not a takedown. It is for the person who looked at Document AI, understood that it is an API sitting inside a Google Cloud project that returns JSON, and wondered whether the same receipt and invoice data is available without building that project. It is, and here is the honest comparison.
Document AI is Google Cloud service for extracting data from documents. It offers general OCR plus specialized processors, including an Invoice parser and an Expense parser. The Invoice parser pulls invoice number, supplier, amounts, tax, and dates, with line items. The Expense parser is the receipt processor, returning date, supplier, total, currency, and line items. Both return structured JSON and are used by calling the API from a Google Cloud project. There is no consumer web app and no spreadsheet output.
The Invoice parser and the Expense parser each cost $10 per 1,000 pages, billed in ten-page increments per document. General Enterprise Document OCR, which returns raw text rather than fields, is cheaper at $1.50 per 1,000 pages, because it does less. There is no standing free tier for the specialized parsers. These figures appeared on the Document AI pricing page in July 2026; confirm on cloud.google.com before you budget.
| Document AI processor | What it returns | Price (July 2026) |
|---|---|---|
| Invoice parser | Invoice fields and line items | $10 per 1,000 pages |
| Expense parser (receipts) | Receipt fields and line items | $10 per 1,000 pages |
| Enterprise Document OCR | Raw text only, no fields | $1.50 per 1,000 pages |
A cent a page for structured invoice or receipt fields is reasonable at volume. As with Textract, the number that is missing is the engineering: the project, the credentials, the processor, and the code that turns JSON entities into spreadsheet rows. For a team with Google Cloud skills that is fine. For a team without them, that work is the actual cost.
No. Document AI returns JSON. The Invoice and Expense parsers give you normalized entities in a structured payload, and turning that into Excel or CSV is your code. There is no download and no QuickBooks-ready file. If you want a spreadsheet at the end rather than an integration to maintain, that missing export is the gap a browser-based tool fills.
They target different documents. The Invoice parser is tuned for supplier invoices and pulls invoice number, supplier, amounts, tax, and due dates with line items. The Expense parser is tuned for receipts and pulls the receipt date, merchant, total, currency, and line items. In Document AI you choose and provision the processor that matches your document type. A receipt-and-invoice tool reads both without you picking a processor, which is one fewer decision and one fewer thing to configure.
Document AI is a platform; ReceiptOCR is a tool. They extract comparable fields from the same documents. The difference is how much you assemble before and after the extraction.
| Capability | Google Document AI | ReceiptOCR |
|---|---|---|
| How you use it | API, called from code | Browser upload, plus an API |
| Setup before first result | GCP project, credentials, processor | Open the page, upload |
| Output | JSON only | Excel, CSV, JSON, QuickBooks |
| Review a field before export | No interface | On-screen review |
| Choosing a processor | Separate invoice and expense parsers | One engine reads both |
| Free tier | None for the parsers | Try before you buy |
| Best fit | Engineers embedding capture at scale | Teams that want the data in a sheet |
Choose Document AI when document processing is part of software you are building on Google Cloud. If you have engineers, you are already in GCP, you process documents at scale, and you want tight control and the option to train custom processors, Document AI is a strong platform with accurate invoice and receipt parsers. Its integration with the rest of Google Cloud, and the ability to extend it with custom and specialized processors, is a real advantage for an engineering-led team.
Choose a browser-based tool when you want the receipt and invoice data, not a platform to produce it. For expenses, receipt OCR software reads them in a browser and the receipt to Excel converter lands them in a sheet. For vendor bills, invoice OCR software pulls header fields and line items. Developers who want a simpler call than the parsers can use the receipt OCR API for the same fields as JSON, and the intelligent document processing overview maps where each approach fits. If you are also weighing the other big cloud engines, the AWS Textract alternative and Azure Document Intelligence alternative make those comparisons, and Google Vision OCR covers the raw-text tier Google itself tells you to leave for the parsers.
The Invoice parser and the Expense parser each cost $10 per 1,000 pages, billed in ten-page increments per document, as listed on the Document AI pricing page in July 2026. General Enterprise Document OCR, which returns raw text only, is $1.50 per 1,000 pages. There is no standing free tier for the specialized parsers. The per-page rate is low; the setup and parsing code are the real cost.
No. Document AI returns JSON. The Invoice and Expense parsers give you normalized entities in a structured payload, and converting that to Excel or CSV is code you write. There is no download button and no QuickBooks file, which is the main gap if your goal is a spreadsheet rather than an integration.
Yes. Document AI requires a Google Cloud project with the API enabled, credentials, and a provisioned processor, and you call it from code. It has no user interface, so a non-developer cannot use it directly. A browser-based alternative removes the project, the credentials, and the parsing code.
They target different documents. The Invoice parser is tuned for supplier invoices and returns invoice number, supplier, amounts, tax, and due dates with line items. The Expense parser is the receipt processor and returns date, merchant, total, currency, and line items. In Document AI you provision the processor that matches your document type; a receipt-and-invoice tool reads both without that choice.
A tool that does the same receipt and invoice extraction but runs in a browser and exports a spreadsheet. ReceiptOCR reads unfamiliar layouts, shows every field for review, exports Excel, CSV, JSON, or a QuickBooks-ready file, and offers a REST API when you want to integrate, all without a Google Cloud project.
Use Document AI when you are an engineering team embedding extraction into software on Google Cloud, processing at scale, and you want control and the option of custom processors. Use a browser-based tool when you want the receipt and invoice data in a spreadsheet today without building and maintaining that pipeline.
The other big cloud OCR API, compared.
A simpler call than the parsers, same fields as JSON.
Turn a pile of receipts into a clean spreadsheet.
Read vendor bills into header fields and line items.
OCR tuned to read receipts into fields.
What the IDP category includes, and which parts you need.
