If you tried Google Document AI for invoices but really want the data in a spreadsheet, InvoicesOCR is the simpler fit. It reads any PDF or scanned invoice with AI and returns the vendor, dates, totals, and every line item as a clean Excel or CSV file in seconds. There is no Google Cloud project to set up, no processor to create, no client library to call, and no JSON to parse. Upload an invoice below and see the line-item data right away.
Upload your receipts and invoices
Drop files here or click to upload
Up to 50 files
Free to try, no account needed to start
Uploading...
Google Document AI is a document processing service on Google Cloud. For invoices it offers the pretrained Invoice Parser, a processor that reads dozens of fields such as supplier name, invoice number, dates, and totals, plus line items, and returns them as a structured Document JSON object with confidence scores and bounding boxes. The extraction is solid, and that is exactly the point: Document AI gives developers a building block to integrate, not a finished invoice-to-spreadsheet tool. To get a usable file out of it you need a Google Cloud project, billing and IAM set up, a processor created in a region, code that calls the API, and more code that maps the Document JSON into the columns you want. For an engineer building extraction into a product on Google Cloud, that is the right tool. For an accountant or AP team that just needs invoices in Excel, it is a lot of setup for a simple job.
Document AI is an API, not an app. Using it means a GCP project, billing enabled, IAM permissions, a created Invoice Parser processor, and a developer to call it. There is no upload-and-download screen for a finance user.
The Invoice Parser hands back fields and line items as a Document object in JSON, with entity types, confidence, and bounding boxes. Turning that into clean Excel columns is more code you write and maintain.
Document AI is metered per page through your Google Cloud bill, and you manage processors, regions, quotas, and batch jobs to Cloud Storage for larger files. That is normal for a cloud service, but it is overhead a small team does not want.
Validation, deduping, retries, a review step, and the export all sit on your side of the line. The processor extracts; everything that makes the data usable in a spreadsheet is your project.
InvoicesOCR does one job well: it turns invoices into spreadsheets. Upload a PDF, scan, or photo in the browser and the AI returns the vendor, invoice number, dates, tax, totals, and full line items as a clean Excel or CSV file. There is no Google Cloud project to create, no processor or client library to configure, and no Document JSON to map into columns. The focus stays on getting invoice data, line items included, into a file your accounting system can import.
It is tuned for vendor invoices and supplier bills, so the fields you care about, vendor, dates, tax, totals, and line items, come out clean.
You get a clean spreadsheet ready for QuickBooks, Xero, or NetSuite, not a Document JSON response you have to parse and reshape in code.
There is nothing to provision and no processor to create. Open the page, upload an invoice, and the data extracts the same minute, right in the browser.
Each line on the invoice becomes its own row, so you get description, quantity, unit price, and amount, not just the header totals.
AI extraction handles PDFs, scans, and phone photos from any supplier in any format, with no template or per-vendor setup.
Files are encrypted and deleted automatically after processing, so invoice data does not linger.
From a supplier invoice to a clean, itemized spreadsheet in about a minute, with no Google Cloud project and nothing to code first.
Drag in PDF, JPG, PNG, or scanned invoices, one at a time or as a batch.
Tip: Multi-page PDFs are supported.
InvoicesOCR reads the vendor, invoice number, dates, tax, totals, and every line item and shows them for a quick check.
Export a clean spreadsheet and import it into your accounting system, or arrange the columns for a specific ERP template.
Tip: The same file works for QuickBooks, Xero, and NetSuite imports.
US accountants, bookkeepers, and finance teams who want vendor invoice data in a spreadsheet, not a cloud document AI service they have to call from code and turn into a file themselves.
Turn client invoices into clean, itemized Excel without a Google Cloud project or a developer to call a processor.
Process the monthly vendor invoice pile into a spreadsheet without building a pipeline on top of Document AI.
Get reliable invoice extraction without provisioning GCP, parsing Document JSON, or maintaining extraction code.
Use the browser tool for ad hoc work and the InvoicesOCR API when an invoice batch needs to run automatically.
Last updated June 2026
Google Document AI is a document processing service on Google Cloud. Its general processors read text, forms, and tables, and the pretrained Invoice Parser is the invoice path: it extracts fields such as supplier name, invoice number, dates, and totals, plus line-item fields like description, quantity, and amount, and returns them inside a Document object as JSON. You call it synchronously for single files, or run batch processing that writes results to a Cloud Storage bucket for larger jobs. If the pretrained parser is not enough, the Document AI Workbench lets engineers train a custom extractor. The extraction is accurate and well documented. The catch is that Document AI is a building block for developers, not a finished tool for finance users. It hands back entities, confidence scores, and bounding boxes, and you write the code that turns that into a spreadsheet, a review screen, and an import file.
InvoicesOCR is built for the opposite starting point. A finance user opens the page, uploads a vendor invoice, and gets clean, itemized data as Excel or CSV. One is a cloud API you integrate; the other is a tool you use directly. If you are an engineer embedding extraction into a product on Google Cloud, Document AI is purpose-built for that. If you want the vendor, dates, tax, totals, and line items in a file you can open, import, or check yourself, InvoicesOCR gets you there the same minute, with nothing to provision.
Using Document AI for invoices means a Google Cloud project, billing enabled, IAM permissions, and an Invoice Parser processor created in a region. Then you write code that sends each file to the processor and handles the Document response, map the entities into the columns you actually want, deal with multi-page and batch jobs to Cloud Storage, add retries and validation, and build the export. That is a normal developer workflow, and at scale it pays off. For an accountant, a bookkeeper, or a smaller AP team, it is infrastructure aimed at a problem they do not have. InvoicesOCR removes all of it: there is no project to create, no processor to manage, and no JSON to reshape. You upload an invoice and download a spreadsheet, and the line items are already laid out as rows.
Document AI returns extracted entities with their types, positions, and confidence, which is exactly what a developer wants in order to build a custom pipeline. It is not what a finance user wants when the goal is a clean file. InvoicesOCR hands you a spreadsheet with one row per line item, including description, quantity, unit price, and amount, alongside the vendor, invoice number, dates, tax, and totals. You decide how each invoice is coded, approved, and paid in your own accounting system. If you later want to automate the extraction step, InvoicesOCR offers an invoice OCR API, so you can start manually today and call the API when a batch needs to run on a schedule, without standing up your own Document AI integration first.
This comparison should be honest. If you are a developer building a custom document pipeline, already run on Google Cloud, and want raw extracted entities with bounding boxes and confidence scores, or you want to train a custom processor in the Document AI Workbench for documents beyond invoices, Google Document AI is an excellent, mature choice, and the Invoice Parser is built specifically for invoices. InvoicesOCR is not a general document AI service or an SDK; it does not return bounding boxes or confidence scores for you to wire into your own UI, and it is not the tool for embedding extraction deep inside another product on Google Cloud. It is focused on invoices and on finance users who want a spreadsheet without writing code. Match the tool to the job before you decide.
For the specific task of turning invoices into spreadsheets, a no-code tool removes the Google Cloud project, the processor, and the JSON mapping, and hands you the line-item file you would otherwise have built. Run a few of your own invoices through it and check the columns before you commit to building on a cloud API.
Teams come to a Google Document AI alternative from very different invoice piles. If most of your bills are component and raw-material invoices tied to purchase orders, the workflow in invoice extraction for manufacturing shows the line-level capture that feeds a three-way match. Finance leaders who want the data rolled into spend visibility rather than raw JSON should read invoice extraction for CFOs, and anyone whose real goal is to stop rekeying fields by hand will find the case in eliminate manual invoice data entry.
"Document AI read the fields well, but we still had to spin up a Google Cloud project, create a processor, and write code to turn the JSON into a spreadsheet. For our team, uploading an invoice and downloading Excel with every line already as a row was all we actually needed."
It depends on the job. Google Document AI is a cloud document processing API for developers building their own pipeline on Google Cloud. If your real need is turning vendor invoices into a spreadsheet, a focused tool like InvoicesOCR is the simpler fit: it reads any invoice layout in the browser and exports Excel or CSV with no GCP project, no processor to create, and no JSON to parse.
Google Document AI is a managed Google Cloud service that extracts text, forms, and tables from documents using processors. For invoices it offers a pretrained Invoice Parser that reads fields such as supplier, invoice number, dates, and totals plus line items and returns them as a structured Document JSON object. It is a building block developers call from code, not a finished invoice-to-spreadsheet application.
Yes. Document AI has a dedicated pretrained Invoice Parser processor that returns supplier, invoice number, dates, totals, and line-item fields. It is accurate, but it gives you a Document JSON to build on, not a spreadsheet. InvoicesOCR is aimed at the next step: it returns the same kind of data as a clean Excel or CSV file you can import, with no code in between.
Not directly. The Invoice Parser returns extracted entities as a Document JSON object, and turning that into an Excel file is code you write and maintain. InvoicesOCR exports Excel or CSV by default, with one row per line item, so there is nothing to assemble. If you need a spreadsheet rather than a JSON response, that is the main reason teams pick a no-code tool over Document AI.
No. Unlike Google Document AI, InvoicesOCR is a browser tool with nothing to provision. There is no GCP project, no billing or IAM to configure, and no processor or client library to install. You open the page, upload an invoice, review the extracted vendor, dates, totals, and line items, and download Excel or CSV. An API is available separately if you later want to automate extraction.
Google Document AI is billed per page through your Google Cloud account, with the pretrained Invoice Parser priced in the range of a cent per page and custom extractors costing more, so check Google Cloud directly for current pricing. On top of per-page charges, factor in the developer time to build and run the integration. InvoicesOCR is built for teams that want straightforward invoice-to-spreadsheet conversion without metering pages or maintaining code.
The browser tool returns a spreadsheet, not JSON, because the goal is a file you can open and import. That is the difference from Document AI, which returns a Document JSON object for developers to parse. If you do want structured data for a program, InvoicesOCR offers an invoice OCR API, so you can choose a ready-made spreadsheet in the browser or structured output through the API.
The Invoice Parser is a pretrained processor in Google Document AI that extracts standard invoice fields, supplier, invoice number, dates, tax, totals, and line items, and returns them as a Document JSON object with confidence scores. It is designed for developers to call from code on Google Cloud. InvoicesOCR covers the same invoice fields but delivers them straight to Excel or CSV, with no processor to create and no JSON to handle.
If your goal is invoice data in a spreadsheet, yes. There is no integration to rebuild and no pipeline to maintain. Upload your invoices, review the extracted vendor, dates, totals, and line items, and download Excel or CSV. Because the tool reads any layout with AI, there is no setup, so your first batch works the same way every batch after it does.
