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microsoft/azure-ai-document-intelligence-dotnet

Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".

What is azure-ai-document-intelligence-dotnet?

azure-ai-document-intelligence-dotnet is a Claude Code agent skill that azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".

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Documentation

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/  # Required: Document Intelligence endpoint
DOCUMENT_INTELLIGENCE_API_KEY=<your-api-key>  # Only required for AzureKeyCredential auth
BLOB_CONTAINER_SAS_URL=https://<storage>.blob.core.windows.net/<container>?<sas-token>  # Optional: blob container SAS URL for training data
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Authentication

Microsoft Entra Token Credential

using Azure.Identity;
using Azure.AI.DocumentIntelligence;

string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
var credential = new DefaultAzureCredential(
    DefaultAzureCredential.DefaultEnvironmentVariableName
);
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/dotnet/api/overview/azure/identity-readme?view=azure-dotnet#credential-classes
// var credential = new ManagedIdentityCredential();
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

ClientPurpose
DocumentIntelligenceClientAnalyze documents, classify documents
DocumentIntelligenceAdministrationClientBuild/manage custom models and classifiers

Prebuilt Models

Model IDDescription
prebuilt-readExtract text, languages, handwriting
prebuilt-layoutExtract text, tables, selection marks, structure
prebuilt-invoiceExtract invoice fields (vendor, items, totals)
prebuilt-receiptExtract receipt fields (merchant, items, total)
prebuilt-idDocumentExtract ID document fields (name, DOB, address)
prebuilt-businessCardExtract business card fields
prebuilt-tax.us.w2Extract W-2 tax form fields
prebuilt-healthInsuranceCard.usExtract 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($"Table: {table.RowCount} rows x {table.ColumnCount} columns");
    foreach (DocumentTableCell cell in table.Cells)
    {
        Console.WriteLine($"  Cell ({cell.RowIndex}, {cell.ColumnIndex}): {cell.Content}");
    }
}

3. Analyze Receipt

Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-receipt", 
    receiptUri);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    if (document.Fields.TryGetValue("MerchantName", out DocumentField merchantField))
        Console.WriteLine($"Merchant: {merchantField.ValueString}");
        
    if (document.Fields.TryGetValue("Total", out DocumentField totalField))
        Console.WriteLine($"Total: {totalField.ValueCurrency.Amount}");
        
    if (document.Fields.TryGetValue("TransactionDate", out DocumentField dateField))
        Console.WriteLine($"Date: {dateField.ValueDate}");
}

4. Build Custom Model

var adminClient = new DocumentIntelligenceAdministrationClient(
    new Uri(endpoint), 
    new AzureKeyCredential(apiKey));

string modelId = "my-custom-model";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var blobSource = new BlobContentSource(blobContainerUri);
var options = new BuildDocumentModelOptions(modelId, DocumentBuildMode.Template, blobSource);

Operation<DocumentModelDetails> operation = await adminClient.BuildDocumentModelAsync(
    WaitUntil.Completed, 
    options);

DocumentModelDetails model = operation.Value;

Console.WriteLine($"Model ID: {model.ModelId}");
Console.WriteLine($"Created: {model.CreatedOn}");

foreach (var docType in model.DocumentTypes)
{
    Console.WriteLine($"Document type: {docType.Key}");
    foreach (var field in docType.Value.FieldSchema)
    {
        Console.WriteLine($"  Field: {field.Key}, Confidence: {docType.Value.FieldConfidence[field.Key]}");
    }
}

5. Build Document Classifier

string classifierId = "my-classifier";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var sourceA = new BlobContentSource(blobContainerUri) { Prefix = "TypeA/train" };
var sourceB = new BlobContentSource(blobContainerUri) { Prefix = "TypeB/train" };

var docTypes = new Dictionary<string, ClassifierDocumentTypeDetails>()
{
    { "TypeA", new ClassifierDocumentTypeDetails(sourceA) },
    { "TypeB", new ClassifierDocumentTypeDetails(sourceB) }
};

var options = new BuildClassifierOptions(classifierId, docTypes);

Operation<DocumentClassifierDetails> operation = await adminClient.BuildClassifierAsync(
    WaitUntil.Completed, 
    options);

DocumentClassifierDetails classifier = operation.Value;
Console.WriteLine($"Classifier ID: {classifier.ClassifierId}");

6. Classify Document

string classifierId = "my-classifier";
Uri documentUri = new Uri("https://example.com/document.pdf");

var options = new ClassifyDocumentOptions(classifierId, documentUri);

Operation<AnalyzeResult> operation = await client.ClassifyDocumentAsync(
    WaitUntil.Completed, 
    options);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    Console.WriteLine($"Document type: {document.DocumentType}, confidence: {document.Confidence}");
}

7. Manage Models

// Get resource details
DocumentIntelligenceResourceDetails resourceDetails = await adminClient.GetResourceDetailsAsync();
Console.WriteLine($"Custom models: {resourceDetails.CustomDocumentModels.Count}/{resourceDetails.CustomDocumentModels.Limit}");

// Get specific model
DocumentModelDetails model = await adminClient.GetModelAsync("my-model-id");
Console.WriteLine($"Model: {model.ModelId}, Created: {model.CreatedOn}");

// List models
await foreach (DocumentModelDetails modelItem in adminClient.GetModelsAsync())
{
    Console.WriteLine($"Model: {modelItem.ModelId}");
}

// Delete model
await adminClient.DeleteModelAsync("my-model-id");

Key Types Reference

TypeDescription
DocumentIntelligenceClientMain client for analysis
DocumentIntelligenceAdministrationClientModel management
AnalyzeResultResult of document analysis
AnalyzedDocumentSingle document within result
DocumentFieldExtracted field with value and confidence
DocumentFieldTypeString, Date, Number, Currency, etc.
DocumentPagePage info (lines, words, selection marks)
DocumentTableExtracted table with cells
DocumentModelDetailsCustom model metadata
BlobContentSourceTraining data source

Build Modes

ModeUse Case
DocumentBuildMode.TemplateFixed layout documents (forms)
DocumentBuildMode.NeuralVariable layout documents

Best Practices

  1. Use DefaultAzureCredential for production
  2. Reuse client instances — clients are thread-safe
  3. Handle long-running operations — Use WaitUntil.Completed for simplicity
  4. Check field confidence — Always verify Confidence property
  5. Use appropriate model — Prebuilt for common docs, custom for specialized
  6. Use custom subdomain — Required for Entra ID authentication

Error Handling

using Azure;

try
{
    var operation = await client.AnalyzeDocumentAsync(
        WaitUntil.Completed, 
        "prebuilt-invoice", 
        documentUri);
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.Message}");
}

Related SDKs

SDKPurposeInstall
Azure.AI.DocumentIntelligenceDocument analysis (this SDK)dotnet add package Azure.AI.DocumentIntelligence
Azure.AI.FormRecognizerLegacy SDK (deprecated)Use DocumentIntelligence instead

Reference Links

ResourceURL
NuGet Packagehttps://www.nuget.org/packages/Azure.AI.DocumentIntelligence
API Referencehttps://learn.microsoft.com/dotnet/api/azure.ai.documentintelligence
GitHub Sampleshttps://github.com/Azure/azure-sdk-for-net/tree/main/sdk/documentintelligence/Azure.AI.DocumentIntelligence/samples
Document Intelligence Studiohttps://documentintelligence.ai.azure.com/
Prebuilt Modelshttps://aka.ms/azsdk/formrecognizer/models

Individual skills in this repo

This repo contains 12 individual skills — each has its own dedicated page.

microsoft/azure-ai-agents-persistent-dotnet

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: "PersistentAgentsClient", "persistent agents", "agent threads", "agent runs", "streaming agents", "function calling agents .NET".

microsoft/azure-ai-openai-dotnet

Azure OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants. Triggers: "Azure OpenAI", "AzureOpenAIClient", "ChatClient", "chat completions .NET", "GPT-4", "embeddings", "DALL-E", "Whisper", "OpenAI .NET".

microsoft/azure-ai-projects-dotnet

Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".

microsoft/azure-ai-voicelive-dotnet

Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant .NET", "bidirectional audio", "speech-to-speech".

microsoft/azure-eventgrid-dotnet

Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents. Triggers: "Event Grid", "EventGridPublisherClient", "CloudEvent", "EventGridEvent", "publish events .NET", "event-driven", "pub/sub".

microsoft/azure-eventhub-dotnet

Azure Event Hubs SDK for .NET. Use for high-throughput event streaming: sending events (EventHubProducerClient, EventHubBufferedProducerClient), receiving events (EventProcessorClient with checkpointing), partition management, and real-time data ingestion. Triggers: "Event Hubs", "event streaming", "EventHubProducerClient", "EventProcessorClient", "send events", "receive events", "checkpointing", "partition".

microsoft/azure-identity-dotnet

Azure Identity library for .NET. Authentication library for Azure SDK clients using Microsoft Entra ID. Use for DefaultAzureCredential, managed identity, service principals, and developer credentials. Triggers: "Azure Identity", "DefaultAzureCredential", "ManagedIdentityCredential", "ClientSecretCredential", "authentication .NET", "Azure auth", "credential chain".

microsoft/azure-kusto-graph

Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

microsoft/azure-kusto-irql

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation events.

microsoft/azure-kusto-irql-graph

Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.

microsoft/azure-local

Plan, deploy, operate, and troubleshoot Azure Local (formerly Azure Stack HCI): sizing and prerequisites, Arc registration, lifecycle updates, workloads (Azure Local VMs, AKS on Azure Local, images, disks, logical networks), SDN and network security, and failure triage — starting read-only and confirming before risky changes. WHEN: Azure Local, Azure Stack HCI, Arc resource bridge, custom location, Azure Local VM, Arc VM, AKS on Azure Local, AKS hybrid, SDN, Lifecycle Manager, Azure Local update, disconnected site.

microsoft/azure-local-multi-rack

Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.

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