If you tried Azure AI Document Intelligence 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 Azure subscription to set up, no Document Intelligence resource to create, no endpoint and key to wire into code, and no JSON to parse. Upload an invoice below and see the line-item data right away.
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Azure AI Document Intelligence, the service Microsoft used to call Form Recognizer, is a cloud document-processing API. For invoices it ships a prebuilt invoice model that reads dozens of fields such as vendor name, invoice ID, dates, tax, and total, plus line items, and returns them as structured JSON. The extraction is strong on standard layouts. The catch is what it takes to use: Document Intelligence is an API component, not a finished app. To get a usable file out of it you create an Azure subscription, spin up a Document Intelligence resource, copy the endpoint and key, and either click around Document Intelligence Studio to test or write REST or SDK code that calls the prebuilt invoice model and maps the JSON into the columns you want. For an engineer building extraction on Azure, that is the right tool. For an accountant or AP team that just needs invoices in Excel, it is a lot of cloud setup for a simple job.
Document Intelligence is an API, not an app. Using it means an Azure subscription, a Document Intelligence resource, the endpoint and key from the Keys and Endpoint page, and a developer to call the prebuilt invoice model. There is no upload-and-download screen for a finance user.
The prebuilt invoice model hands back fields and line items as a JSON response with confidence scores and bounding regions. Turning that into clean Excel columns is more code you write and maintain.
Document Intelligence is metered per page on your Azure bill, with a small free monthly allowance and commitment tiers at volume. You manage the resource, region, keys, and quotas. That is normal for a cloud service, but it is overhead a small team does not want.
Validation, retries, a review step, and the export all sit on your side. Studio is handy for testing a few files, but a production invoice-to-spreadsheet flow is still an integration you build and keep running.
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 Azure subscription to create, no Document Intelligence resource or endpoint to configure, and no 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 JSON response you have to parse and reshape in code.
There is nothing to provision and no endpoint to wire up. 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 Azure resource 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 provision, call from code, and turn into a file themselves.
Turn client invoices into clean, itemized Excel without an Azure resource or a developer to call the prebuilt invoice model.
Process the monthly vendor invoice pile into a spreadsheet without building a pipeline on top of Document Intelligence.
Get reliable invoice extraction without provisioning Azure, parsing 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
Azure AI Document Intelligence is the service Microsoft formerly branded Form Recognizer, now grouped under its Foundry tools. It reads text, key-value pairs, and tables from documents using prebuilt and custom models, and the prebuilt invoice model is the invoice path: it extracts fields such as vendor name, invoice ID, invoice and due dates, tax, and total, plus line-item fields like description, quantity, unit price, and amount, and returns them as JSON. You can test a file or two in Document Intelligence Studio, but production use means calling the model from the REST API or an SDK with your resource endpoint and key. If the prebuilt model is not enough, you can train a custom model in Studio. The extraction is accurate on standard invoices and well documented. The catch is that Document Intelligence is a building block for developers, not a finished tool for finance users. It returns entities, confidence scores, and bounding regions, 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 Azure, Document Intelligence 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 Intelligence for invoices means an Azure subscription, a Document Intelligence resource created in a region, and the endpoint and key copied from the Keys and Endpoint page. Then you write code that sends each file to the prebuilt invoice model and handles the JSON response, maps the fields into the columns you actually want, deals with multi-page documents, adds retries and validation, and builds 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 subscription to create, no resource or key 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 Intelligence returns extracted fields 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 Intelligence integration first.
This comparison should be honest. If you are a developer building a custom document pipeline, already run on Azure, and want raw extracted fields with bounding regions and confidence scores, or you want to train a custom model in Document Intelligence Studio for documents beyond invoices, Azure AI Document Intelligence is an excellent, mature choice, and the prebuilt invoice model is built specifically for invoices. InvoicesOCR is not a general document AI service or an SDK; it does not return bounding regions 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 Azure. 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 Azure resource, the endpoint and key, 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.
The reason behind an evaluation usually points to a clear next step. Buyers who match invoices to a purchase order can see the workflow on invoice processing for procurement managers. Teams whose goal is simply to stop keying can read how to eliminate manual invoice data entry, and AP groups fighting short-pays and chargebacks can see how accurate capture helps resolve vendor payment disputes.
"Document Intelligence read the fields well, but we still had to create an Azure resource, copy the endpoint and key, 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. Azure AI Document Intelligence is a cloud document processing API for developers building their own pipeline on Azure. 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 Azure resource, no endpoint or key to wire up, and no JSON to parse.
Azure AI Document Intelligence, formerly Form Recognizer, is a managed Azure service that extracts text, key-value pairs, and tables from documents using prebuilt and custom models. For invoices it offers a prebuilt invoice model that reads fields such as vendor, invoice ID, dates, tax, and total plus line items and returns them as JSON. It is a building block developers call from code, not a finished invoice-to-spreadsheet application.
Yes. Form Recognizer is the former name of the service Microsoft now calls Azure AI Document Intelligence. The prebuilt invoice model and the developer workflow, create a resource, get an endpoint and key, call the API, parse the JSON, are the same idea. InvoicesOCR is an alternative to both names: it reads invoices and exports a spreadsheet directly, with no Azure resource and no code.
Not directly. The prebuilt invoice model returns extracted fields as a JSON response, 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 Intelligence.
No. Unlike Azure Document Intelligence, InvoicesOCR is a browser tool with nothing to provision. There is no Azure subscription, no Document Intelligence resource, and no endpoint or key to configure. 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.
Azure Document Intelligence is billed per page through your Azure account, with a small free monthly page allowance and volume commitment tiers, so check Azure 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 Intelligence, which returns a JSON response 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 prebuilt invoice model is a ready-to-use model in Azure Document Intelligence that extracts standard invoice fields, vendor, invoice ID, dates, tax, total, and line items, and returns them as JSON with confidence scores. It is designed for developers to call from the REST API or an SDK. InvoicesOCR covers the same invoice fields but delivers them straight to Excel or CSV, with no resource 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.
