azure-ai-document-intelligence-dotnet
Extracts text, tables, and data from documents. It uses pre-built or custom models to understand file content.
What it does
This tool helps extract important information from documents like invoices, receipts, and ID cards. It can read text, tables, and structured data.
When to use it
- ✓To automatically organize invoices and receipts.
- ✓To extract data from identification documents.
- ✓To read text and tables from any document.
Example of what to ask your AI
“Extract the vendor name and total amount from the PDF invoice.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You provide a document (like a PDF or image) and choose a pre-built model (like 'invoice' or 'receipt'). The tool then reads the document and returns the information you requested.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill azure-ai-document-intelligence-dotnetOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/azure-ai-document-intelligence-dotnet/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Azure.AI.DocumentIntelligence (.NET)
Extract text, tables, and structured data from documents using prebuilt and custom models.
Installation
dotnet add package Azure.AI.DocumentIntelligence
dotnet add package Azure.Identity
Current Version: v1.0.0 (GA)
Environment Variables
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource-name>.cognitiveservices.azure.com/
DOCUMENT_INTELLIGENCE_API_KEY=<your-api-key>
BLOB_CONTAINER_SAS_URL=https://<storage>.blob.core.windows.net/<container>?<sas-token>
Authentication
Microsoft Entra ID (Recommended)
using Azure.Identity;
using Azure.AI.DocumentIntelligence;
string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
var credential = new DefaultAzureCredential();
var client = new DocumentIntelligenceClient(new Uri(endpoint), credential);
Note: Entra ID requires a custom subdomain (e.g.,
https://<resource-name>.cognitiveservices.azure.com/), not a regional endpoint.
API Key
string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_API_KEY");
var client = new DocumentIntelligenceClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
Client Types
| Client | Purpose |
|---|---|
DocumentIntelligenceClient |
Analyze documents, classify documents |
DocumentIntelligenceAdministrationClient |
Build/manage custom models and classifiers |
Prebuilt Models
| Model ID | Description |
|---|---|
prebuilt-read |
Extract text, languages, handwriting |
prebuilt-layout |
Extract text, tables, selection marks, structure |
prebuilt-invoice |
Extract invoice fields (vendor, items, totals) |
prebuilt-receipt |
Extract receipt fields (merchant, items, total) |
prebuilt-idDocument |
Extract ID document fields (name, DOB, address) |
prebuilt-businessCard |
Extract business card fields |
prebuilt-tax.us.w2 |
Extract W-2 tax form fields |
prebuilt-healthInsuranceCard.us |
Extract health insurance card fields |
Core Workflows
1. Analyze Invoice
using Azure.AI.DocumentIntelligence;
Uri invoiceUri = new Uri("https://example.com/invoice.pdf");
Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
WaitUntil.Completed,
"prebuilt-invoice",
invoiceUri);
AnalyzeResult result = operation.Value;
foreach (AnalyzedDocument document in result.Documents)
{
if (document.Fields.TryGetValue("VendorName", out DocumentField vendorNameField)
&& vendorNameField.FieldType == DocumentFieldType.String)
{
string vendorName = vendorNameField.ValueString;
Console.WriteLine($"Vendor Name: '{vendorName}', confidence: {vendorNameField.Confidence}");
}
if (document.Fields.TryGetValue("InvoiceTotal", out DocumentField invoiceTotalField)
&& invoiceTotalField.FieldType == DocumentFieldType.Currency)
{
CurrencyValue invoiceTotal = invoiceTotalField.ValueCurrency;
Console.WriteLine($"Invoice Total: '{invoiceTotal.CurrencySymbol}{invoiceTotal.Amount}'");
}
// Extract line items
if (document.Fields.TryGetValue("Items", out DocumentField itemsField)
&& itemsField.FieldType == DocumentFieldType.List)
{
foreach (DocumentField item in itemsField.ValueList)
{
var itemFields = item.ValueDictionary;
if (itemFields.TryGetValue("Description", out DocumentField descField))
Console.WriteLine($" Item: {descField.ValueString}");
}
}
}
2. Extract Layout (Text, Tables, Structure)
Uri fileUri = new Uri("https://example.com/document.pdf");
Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
WaitUntil.Completed,
"prebuilt-layout",
fileUri);
AnalyzeResult result = operation.Value;
// Extract text by page
foreach (DocumentPage page in result.Pages)
{
Console.WriteLine($"Page {page.PageNumber}: {page.Lines.Count} lines, {page.Words.Count} words");
foreach (DocumentLine line in page.Lines)
{
Console.WriteLine($" Line: '{line.Content}'");
}
}
// Extract tables
foreach (DocumentTable table in result.Tables)
{
Console.WriteLine($"Table: {table.RowCount} rows x {table.ColumnCount} columns");
foreach (DocumentTableCell cell in table.Cells)
{
…
FAQ
What are 'pre-built models'?
These are models that the tool already understands, trained to recognize specific document types like invoices or receipts.
Can I use my own documents to train the tool?
Yes, you can create custom models for documents not covered by the pre-built ones.
Where are the extracted information saved?
The tool extracts the information and returns it for you to use in your program. How it's saved depends on how you set up your code.
Details
Original description by the author
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2270
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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