2.1 Project Overview

Overview of Project ☁️

Scenario

A startup is building a photo-sharing application where users upload images daily.

They need a system that can:

  • Automatically detect objects and scenes in images.
  • Generate meaningful descriptions for photos.
  • Organize images based on their content.

However, they don’t want to build and train machine learning models from scratch. Instead, they are looking for a simple, scalable AI-powered solution using cloud services.

Our Solution

We’ll build an AI-powered image analysis application on Microsoft Azure that:

  • Hosts the frontend using Azure Static Web Apps.
  • Uses Azure Functions to handle backend API requests.
  • Integrates Azure AI Vision to analyze images and extract insights.
  • Returns structured results like tags and captions to the user interface.

This approach allows the application to deliver intelligent features without managing or training ML models.

About Project

In this project, you’ll learn how to integrate AI services into a real-world application.

  • These concepts are important because modern applications increasingly rely on pre-built AI services instead of building models from scratch.
  • You’ll learn to:
    • Use Azure AI Vision for image analysis.
    • Build backend APIs using Azure Functions.
    • Connect frontend applications with AI-powered services.
    • Process and display AI-generated insights.

By the end, you’ll have hands-on experience building an intelligent cloud application, a key step toward AI-powered systems.

Steps To Be Performed 👩‍💻

We’ll go through the following steps in the next lessons:

  1. Create and configure Azure AI Vision.
  2. Build backend APIs using Azure Functions.
  3. Send images to the AI service for analysis.
  4. Create a frontend to upload images.
  5. Display tags and captions in the UI.
  6. Test the complete application.

Services Used 🛠

  • Azure Static Web Apps → Hosts the frontend.
  • Azure Functions → Handles backend API logic.
  • Azure AI Vision → Analyzes images and returns insights.

Estimated Time & Cost ⚙️

  • Estimated time: ~2 hours.
  • Cost: Free or minimal (within Azure free tier).

➡️ Architectural Diagram

This is the architectural diagram for the project:

➡️ Final Result

By the end of this project, you will have built a working AI-powered photo inspector using Azure.

Here’s what you’ll learn:

  • Integrate AI into real-world applications.
  • Analyze images using cloud-based services.
  • Build serverless APIs for AI workflows.
  • Connect frontend, backend, and AI services.

This project introduces you to building intelligent applications using cloud AI services.

Complete and Continue