AWS Textract vs Google Document AI: Receipt and Invoice OCR Compared

Last updated July 2026.

AWS Textract and Google Document AI both extract receipt and invoice data accurately, and for most teams the choice comes down to which cloud you already build on. Textract bills its AnalyzeExpense API at one cent per page; Google charges ten dollars per 1,000 pages for its Invoice and Expense parsers, which works out to the same one cent. Both return JSON only, both need a cloud project and code, and neither exports a spreadsheet. If you have engineers, pick the cloud you are on. If you just want the data in Excel, neither is really built for you.

AWS Textract vs Google Document AI at a glance

The two services are more alike than different. Both are cloud OCR platforms with a document API, both have processors tuned for receipts and invoices, and both hand back structured JSON you build around. Here is the honest side by side, with pricing verified from each vendor's own page in July 2026.

Which is better, AWS Textract or Google Document AI?

Neither is clearly better; the right pick is the cloud you already run on. Textract and Document AI extract comparable receipt and invoice fields at the same effective price of about one cent per page, and both return JSON you have to turn into a usable spreadsheet yourself. If your stack is AWS, Textract removes a second vendor and integrates with S3 and Lambda. If your stack is Google Cloud, Document AI does the same. The decision is about your existing infrastructure and team skills, not a meaningful accuracy or cost gap between the two.

How does the pricing compare?

The headline rates land in the same place. Textract AnalyzeExpense is $0.01 per page for the first million pages a month and $0.008 above that. Google's Invoice and Expense parsers are $10 per 1,000 pages, which is also $0.01 per page, billed in ten-page increments per document. The difference is at the edges. Textract offers a 100-page monthly free tier for the first three months, while Google has no standing free tier for its parsers. Google does bill in ten-page blocks, so a two-page receipt still rounds within its increment, which slightly favors documents that fill the block. At volume, both are cheap per page and the meaningful cost is engineering, not the rate.

Do Textract and Document AI handle receipts and invoices?

Yes, both do, with a small structural difference. Textract uses a single API, AnalyzeExpense, for both receipts and invoices, returning summary fields such as vendor, total, tax, and date, plus line item groups. Google splits the job into two processors: the Invoice parser for supplier bills and the Expense parser for receipts, each provisioned separately. So with Textract you call one endpoint for mixed documents, while with Document AI you choose and provision the processor that matches the document type. Both extract header fields and line items reliably.

Do they export to Excel or CSV?

No. Both return JSON and nothing else. Textract's ExpenseDocuments and Google's normalized entities are structured payloads meant to be consumed by code, and getting either into an Excel or CSV file, or a QuickBooks-ready import, is work you do yourself. There is no download button in either service. If a spreadsheet is the actual goal, this shared gap matters more than any difference between the two, and it is the reason a browser-based extraction tool exists alongside the raw APIs.

Which is more accurate on receipts?

In practice they are close, and both are strong on clean printed receipts and invoices. Accuracy on either drops on the same hard inputs: faded thermal paper, skewed phone photos, and low-contrast scans. Independent results shift with each model update, so treating one as decisively more accurate than the other is usually overfitting to a single test set. The more useful question is what happens after extraction, because neither API shows you a field to confirm before it flows downstream. A review step, wherever it lives, is what protects the books from a single misread total.

Can you use them without code?

Not directly. Both Textract and Document AI are headless APIs with no user interface. You authenticate with cloud credentials, send the document from storage or as bytes, and parse the JSON in your own application. A developer can wire either up in an afternoon; a bookkeeper or office manager cannot use them at all without an engineer. This is the single most common reason teams that evaluated the cloud APIs end up choosing a tool they can open in a browser instead. Teams that also process bank statements hit the same wall there and often reach for a way to turn a PDF bank statement into clean CSV rows without writing a parser, for exactly the same reason.

When a browser tool beats both

If you are building document capture into software at scale and you already live in AWS or Google Cloud, the cloud APIs are the right primitives, and you should pick the one that matches your stack. If your goal is the receipt and invoice data itself, in a spreadsheet, without provisioning a project or writing a parser, a purpose-built tool gets you there faster. 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 either cloud API can use the receipt OCR API for the same fields as JSON. For the full side by side with a browser alternative, see the AWS Textract alternative and the Google Document AI alternative pages.

The bottom line

AWS Textract and Google Document AI are two good answers to the same question, priced almost identically and separated mainly by which cloud you already use. Both nail receipts and invoices, both stop at JSON, and both assume you have engineers to finish the job. Choose Textract on AWS, Document AI on Google Cloud, and a browser tool when you want the data in a spreadsheet without building the pipeline in between.