Using Azure AI to Turn Documents into Actionable Insights
Using Azure AI to Turn Documents into Actionable Insights by Umesh Pandit

Using Azure AI to Turn Documents into Actionable Insights

I want to show you how Azure AI Document Intelligence turns documents into data. With AI and machine learning, this tool helps you make decisions, extract insights, and streamline document processes. Using computer vision, OCR, and NLP, Azure AI Document Intelligence analyzes and extracts data from various document types, enhancing productivity and reducing errors.

What is Document Intelligence?

Document intelligence is an extension of OCR technology that identifies text in scanned documents and comprehends the structure of the information. This advanced capability also enables organizations to turn several manual processes such as entering receipt data in a database into automated processes.

Key Features

  1. Document Classification: Automatically classifies documents based on content, routing them to the appropriate departments.
  2. Information Extraction: Extracts structured data from unstructured documents, capturing key details like dates, invoice numbers, and amounts.
  3. Customization: Customizable to fit specific document processing needs with custom models.
  4. Integration: Seamlessly integrates with other Azure services, fitting into existing workflows and applications.
  5. Key-Value Pair Extraction: Identifies and extracts key-value pairs, useful for forms and contracts.

Getting Started

Now let’s get started with Azure AI Document Intelligence. Here are the steps to get up and running. We’ll cover setting up your account, accessing the Document Intelligence platform, using pre-built models, creating custom models, integrating with other Azure services, testing, deploying, and optimizing.

1. Access Document Intelligence

  • Log in to Azure and search for the "AI Document Intelligence” service.

AI Document Intelligence in Azure

  • Select “Create Document Intelligence”, and fill in general details like subscription, name, pricing tire, etc.
  • Hit the “Review + Create button”.

Create Document Intelligence in Azure

2. Use Pre-built Models

  • Pre-built Models In the Document Intelligence platform, check out the pre-built models for tasks like text extraction, key phrase extraction and entity recognition.
  • To find these, go to the Form Recognizer resource and select "Quickstart". These are ready to use and give instant value without training.
  • Full documentation and examples are available to help you get started and integrate these models into your apps. This includes step-by-step guides, API references, and best practices.

Read more at: https://umeshpandit.hashnode.dev/using-azure-ai-to-turn-documents-into-actionable-insights

Subscribe to my newsletter to read more articles from Umesh Pandit’s Notes directly in your inbox.

MORE ARTICLES

How to Integrate Microsoft's Responsible AI and Copyright Policies

Security Enhancements in Azure: Addressing Emerging Threats

Personal Insights: How Azure DevOps Changed Our Workflow

Simplifying Location Services with Azure Maps and AI Integration

Mastering Azure Security for Robust Cloud Data Protection

Powering High-Performance AI Applications with Azure Database for PostgreSQL

Mastering Azure Kubernetes Service (AKS): Latest Updates and Best Practices for Seamless Deployment

Connect with me on LinkedIn

#AzureAIDocumentIntelligence #DocumentProcessingRevolution #AIInsights #MachineLearningInAction #DataExtractionTech #FormRecognizerFeatures #IntelligentDocumentProcessing #AzureIntegration #AutomateWithAI #UmeshPandit #AzureTalks #umeshpanditax #DXC #WeareDXC


要查看或添加评论,请登录

Dr. Umesh Pandit的更多文章

社区洞察

其他会员也浏览了