🧠 IntelliVision — AI-Powered Document Intelligence Platform

End-to-end AI system for OCR, summarization, and object detection with a scalable microservice architecture.

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🚀 Overview

IntelliVision is a production-ready AI document intelligence system that processes files (images, PDFs) and extracts:

• 📄 Text (OCR)
• 🧠 Summaries
• 🖼️ Detected objects

It is built using a distributed microservice architecture with parallel processing, Redis-backed queues, and secure REST APIs, enabling fast and scalable document analysis.

This project demonstrates real-world backend engineering, AI pipeline design, and system scalability.

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✨ Features

• 🔍 OCR using vision models
• 🧠 Text summarization using NLP models
• 🖼️ Object detection on images
• ⚡ Parallel async processing pipeline
• 🔐 JWT-based authentication
• 📦 Redis caching + job queue
• 🗂️ Processing history & result storage
• 🌐 Fully deployed (cloud-ready)

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🏗️ Architecture

Frontend (React + Vercel)
│
▼
API Gateway (Node.js + Express) ── JWT Auth
│
├── Redis Cache / Job Queue
│
▼
AI Processor (FastAPI)
├── OCR Service
├── Summarization Service
└── Object Detection
│
▼
PostgreSQL (Results & History)

Explaining Architecture

• Microservices → independent scaling
• Redis queue → non-blocking async jobs
• Parallel execution → reduced latency
• Stateless APIs → cloud-friendly deployment

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🛠️ Tech Stack

Frontend

• React
• Tailwind CSS
• Axios

Backend

• Node.js
• Express.js
• FastAPI (Python)

AI / ML

• OCR (Vision models)
• NLP summarization
• Object detection models

Infrastructure

• Redis (cache + queue)
• PostgreSQL
• Docker
• Render (backend)
• Vercel (frontend)

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📂 Project Structure

IntelliVision/
│
├── frontend/
│   ├── src/
│   ├── public/
│   ├── package.json
│   └── vite.config.js
│
├── gateway/
│   ├── src/
│   │   ├── controllers/
│   │   ├── routes/
│   │   ├── middleware/
│   │   └── services/
│   ├── package.json
│   └── server.js
│
├── worker/
│   ├── src/
│   ├── package.json
│
├── processor/
│   ├── app/
│   └── main.py
│
├── models/
│   └── yolov8n.pt
│
├── docker-compose.yml
├── .gitignore
└── README.md

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⚡ Performance Highlights

• 🚀 ~38% latency reduction via parallel async execution
• ⚡ Redis caching prevents duplicate processing
• 📈 Handles concurrent uploads efficiently
• 🔄 Stateless services allow horizontal scaling

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🔐 Security

• JWT-based authentication
• Secure environment variables
• No secrets committed to repository
• Ready for role-based access control

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🌍 Deployment

Backend

• Render (Node.js Gateway + FastAPI Processor)

Frontend

• Vercel

Data Stores

• Redis Cloud
• PostgreSQL (Neon / Supabase)

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🧪 Running Locally

git clone https://github.com/manishraj-003/IntelliVision
cd IntelliVision
docker-compose up --build

Backend: http://localhost:8000
Frontend: http://localhost:5173

🧠 Key Learnings
-Designing distributed AI pipelines
-Implementing async job queues
-Scaling with Redis
-Secure API design
-Cloud-native deployment workflows

🏁 Conclusion
IntelliVision is a real-world AI SaaS system, not a demo app.
It demonstrates backend depth, system design, and applied AI engineering — the same skills used in modern product companies.