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Azure-Based CV Analysis Service

System Architecture

Core Functionality

This application automates the transition from raw PDF files to searchable database records. It handles the entire lifecycle: uploading, secure storage, AI-driven extraction, and database persistence.

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How It Works

  1. Ingestion & Storage: The Flask backend receives a PDF and uploads it to Azure Blob Storage.
  2. Secure Access: The app generates a SAS (Shared Access Signature) token, giving the AI service temporary, secure access to the private file.
  3. AI Extraction: Azure Document Intelligence parses the PDF and returns specific data points (skills, experience, contact info) as JSON.
  4. Database Storage: Flask receives the JSON and saves it directly into a MongoDB Atlas cluster.

Tech Stack

  • Backend: Python (Flask)
  • Storage: Azure Blob Storage
  • AI/ML: Azure Document Intelligence
  • Database: MongoDB Atlas