Intelligent Document Processing with Microsoft AI

In this article, we will take a close look at intelligent document processing using Microsoft AI to automate and accelerate document processing at your company.

Mariia is a skilled and certified Dynamics 365 Developer with hands-on experience across Dynamics 365, Power Platform, Azure, AI, and a wide range of other Microsoft technologies.

Manual data entry is still among the most inefficient and mistake-prone activities. Businesses process thousands of documents daily, such as invoices, contracts, ID cards, and tax forms, often manually retyping information from PDFs into databases. Microsoft’s Azure AI Document Intelligence, formerly Azure Form Recognizer, effectively copes with this challenge.

This technology goes far beyond simple text recognition: it understands the structure of a document, extracts specific data points, and integrates seamlessly with the Power Platform ecosystem.

Azure AI Document Intelligence is a cloud Machine Learning service designed to extract text, tables, key-value pairs, and structural elements from documents.

Unlike traditional OCR (Optical Character Recognition), which only reads text, this AI understands context, for example, recognizing that a number next to the word “Total” is likely an invoice amount rather than a random value.

Azure AI Document Intelligence is a cloud Machine Learning service designed to extract text, tables, key-value pairs, and structural elements from documents.

Unlike traditional OCR (Optical Character Recognition), which only reads text, this AI understands context, for example, recognizing that a number next to the word “Total” is likely an invoice amount rather than a random value.

1. Document classification

   The AI can analyze a batch of mixed files and automatically sort them (e.g., distinguishing an Invoice from a Purchase Order or a Contract).

2. Data extraction

   It pulls structured data such as dates, addresses, invoice numbers, and line items from tables.

3. Support for various formats

   It accepts PDFs, images (JPG, PNG), and TIFF files.

4. Pre-built vs. custom model

   Microsoft provides ready-to-use models for common documents (Invoices, IDs, Receipts), but you can also train a custom model on your company’s specific forms with just a few sample documents.

Let us imagine a typical scenario: a logistics company receives hundreds of vendor invoices via email every week. The problem is that an accountant opens each email, downloads the PDF, and manually types the vendor's name, date, and total amount into the ERP system.

Here is the AI solution flow:

1. Ingestion

   A vendor sends an invoice to a dedicated email address.

2. Trigger

   Power Automate detects the email and grabs the attachment.

   

3. Processing

   The file is sent to the AI Builder (Document Processing model), which classifies the document as an invoice and extracts the vendor's name, due date, and total amount.

4. Validation

   If the AI’s confidence score is high (e.g., >90%), the data is automatically pushed to the database (Dataverse or SQL).

5. Exception handling

   If the confidence is low, a task is created in a Power App for a human to review and verify the data.

Integrating this technology into Power Apps is straightforward thanks to AI Builder. You do not need to write a complex Python or C# code.

Step 1 Create a model.

Go to the "AI Hub" in the Power Apps maker portal. Choose the "Extract information from documents."

Step 2 Train the model.

Upload at least 5 samples of your document. Tag the fields you want to extract (e.g., "Client Name," "Order ID"). Train the model.

Step 3 Integrate.

Once published, you can use the model directly in the Canvas App.

Insert the Form Processor component from the "AI Builder" menu.

Connect it to your trained model.

Step 4 Use the data.

When a user uploads a PDF to the app, the component returns the data as properties (e.g., FormProcessor1.Fields.TotalAmount). You can then save this data directly to your CRM or database with a simple formula.

UDS blog articles:

• AI-powered Document Recognition
• Training and Deploying Custom AI Models for Specific Business Application
• Dynamic AI Assistant for Invoicing

UDS case studies:

• AI Assistant for Invoice Processing

UDS services:

• AI Assistance Service