Automated Document Processing with Azure Document Intelligence

Introduction

Processing large volumes of documents manually is time-consuming and error-prone. Whether dealing with invoices, receipts, contracts, or business forms, extracting structured data efficiently is crucial for automation.

Azure Document Intelligence (formerly Azure Form Recognizer) is a cloud-based AI service that enables automated document processing using pre-trained and custom models. With just an API call, you can:

• ✅ Extract key-value pairs from structured forms.
• ✅ Process invoices, receipts, and business cards.
• ✅ Recognize handwritten text and printed text.
• ✅ Automate data extraction into databases or applications.

This article walks through setting up Azure Document Intelligence, sending a document for analysis, and visualizing extracted data.

1️⃣ Setting Up Azure Document Intelligence

Before sending documents for processing, you need to set up Azure Document Intelligence in the Azure Portal.

Steps to Create a Document Intelligence Resource

1️⃣ Log in to Azure Portal.

2️⃣ Click "Create a resource" → Search for "Document Intelligence".

3️⃣ Select "Cognitive Services → Document Intelligence".

4️⃣ Configure the details:

• Subscription: Select an active Azure subscription.
• Resource Group: Create or use an existing one.
• Region: Pick a region closest to your users.
• Pricing Tier: Choose "Standard" or "Free (F0)" for limited usage.

5️⃣ Click "Review + Create" → then "Create".

Once deployed, navigate to "Keys and Endpoint" in the Document Intelligence resource to get:

• ✔ API Key (used for authentication)
• ✔ Endpoint URL (base URL for sending API requests)
  

2️⃣ Sending a Document to Azure Document Intelligence API

Now that the resource is set up, it's time to upload a document (PDF, image, or scanned document) for analysis.

Here’s a Python script to send a document to Azure Document Intelligence API:

import requests

# Replace with your Azure API details
API_KEY = "<your_api_key>"
ENDPOINT = "<your_endpoint>/formrecognizer/documentModels/prebuilt-invoice/analyze?api-version=2023-07-31-preview"

headers = {
    "Ocp-Apim-Subscription-Key": API_KEY,
    "Content-Type": "application/pdf"
}

# Open a sample PDF file
with open("sample_invoice.pdf", "rb") as file_data:
    response = requests.post(ENDPOINT, headers=headers, data=file_data)

# Get operation location (needed to retrieve results)
operation_url = response.headers["Operation-Location"]
print(f"Processing started: {operation_url}")

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📌 What’s Happening?

• The script uploads a document (PDF) to the API.
• The response returns an Operation-Location URL, which is needed to retrieve results later.

3️⃣ Retrieving & Parsing Extracted Data

After submitting a document, the API takes a few seconds to process it. The next step is retrieving the extracted data.

import time
import requests

# Wait for processing to complete
time.sleep(5)

# Retrieve results from Operation-Location
response = requests.get(operation_url, headers={"Ocp-Apim-Subscription-Key": API_KEY})
result = response.json()

print("Extracted Document Data:")
print(result)

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📌 What’s Happening?

• The script waits for processing to complete.
• It retrieves the extracted text in JSON format.

🔗 Azure Docs: Document Intelligence API Reference

4️⃣ Extracting Key Fields from Documents

The API returns structured data, which can be filtered for important key-value pairs such as invoice numbers, dates, and totals.

📌 Example Output

5️⃣ Visualizing Extracted Data

To better understand extracted document data, you can visualize it in a table or chart.

Using Pandas to Display Data in a Table

import pandas as pd

# Create a DataFrame
df = pd.DataFrame([
    {"Invoice Number": invoice_number, "Total Amount": total_amount, "Invoice Date": invoice_date}
])

print(df)

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6️⃣ Automating Document Processing Workflows

Once the extracted data is available, you can:

• ✅ Save it to a database for future reference.
• ✅ Integrate with Power Automate for real-time invoice processing.
• ✅ Use Azure Logic Apps to send automated email alerts.

For example, integrating Azure Logic Apps can send an email when an invoice total exceeds a threshold:

• 1️⃣ Go to Azure Logic Apps in Azure Portal.
• 2️⃣ Create a new Logic App → Choose a Trigger (e.g., "When a file is added to OneDrive").
• 3️⃣ Add an Action → Select "Send Email" (via Outlook, SendGrid, etc.).
• 4️⃣ Configure the email body with extracted invoice details.
• 5️⃣ Save and test the workflow.

🚀 Conclusion

Azure Document Intelligence simplifies automated document processing by extracting structured data from invoices, receipts, and contracts. With just an API call, you can:

• ✅ Convert scanned documents into structured data.
• ✅ Automate invoice processing and financial workflows.
• ✅ Integrate with databases, CRMs, and automation tools.

🔗 Further Learning

• Azure Document Intelligence Overview
• Azure Document Intelligence Q&A