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TalentSync AI - Unified Career, Skills & Hiring Platform

A comprehensive, AI-driven recruitment, placement, learning, and hiring ecosystem platform built with Next.js 14, TypeScript, and Tailwind CSS.

🎯 Overview

TalentSync AI is an enterprise-grade platform featuring three major user roles:

  • Candidate Portal: Job discovery, AI resume analysis, aptitude tests, AI interviews, learning resources
  • College Portal: Student management, campus drive coordination, placement analytics
  • Corporate Portal: Job posting, AI screening, workflow automation, candidate management

✨ Key Features

For Candidates

  • 🎯 AI-powered job matching with skill-based scoring
  • 📄 Resume analysis and optimization
  • 🧠 Aptitude test system with analytics
  • 🤖 AI-powered interview simulation
  • 📚 Career roadmaps and learning resources
  • 📊 Application tracking with detailed timeline

For Colleges

  • 👥 Student pool management
  • 🏢 Campus drive coordination
  • 📅 Logistics and event scheduling
  • 📈 Placement analytics and reports
  • 📑 Document repository

For Corporates/HR

  • 💼 Job posting system (on-campus/off-campus)
  • 🔍 AI-powered candidate screening
  • ⚙️ Customizable hiring workflow
  • 👤 Candidate management dashboard
  • 📊 Hiring analytics and insights

🛠️ Technology Stack

  • Framework: Next.js 14 with App Router
  • Language: TypeScript
  • Styling: Tailwind CSS with custom design system
  • UI Components: Custom component library
  • Icons: Lucide React
  • Animations: Framer Motion
  • Charts: Recharts

🎨 Design Features

  • Professional blue-purple-cyan gradient color palette
  • Dark/Light mode support
  • Fully responsive design (mobile, tablet, desktop)
  • Glassmorphism effects
  • Smooth animations and transitions
  • Accessible UI components

📁 Project Structure

talentsync-ai/
├── app/
│   ├── (auth)/              # Authentication pages
│   ├── candidate/           # Candidate portal pages
│   │   ├── dashboard/
│   │   ├── jobs/
│   │   ├── applications/
│   │   ├── career-assistant/
│   │   ├── aptitude/
│   │   ├── interview/
│   │   └── learning/
│   ├── college/             # College portal pages
│   │   └── dashboard/
│   ├── corporate/           # Corporate portal pages
│   │   └── dashboard/
│   ├── layout.tsx
│   ├── page.tsx             # Landing page
│   └── globals.css
├── components/
│   ├── layouts/             # Layout components
│   │   ├── CandidateLayout.tsx
│   │   ├── CollegeLayout.tsx
│   │   └── CorporateLayout.tsx
│   └── ui/                  # Reusable UI components
│       ├── Button.tsx
│       ├── Card.tsx
│       ├── Input.tsx
│       ├── Modal.tsx
│       ├── Toast.tsx
│       ├── Loading.tsx
│       └── EmptyState.tsx
├── lib/
│   ├── types.ts             # TypeScript type definitions
│   └── data/
│       └── mock-data.ts     # Sample data for demo
├── public/
├── tailwind.config.ts
├── tsconfig.json
└── package.json

🚀 Getting Started

Prerequisites

  • Node.js 18+ and npm/yarn/pnpm

Installation

  1. Clone the repository or navigate to the project directory:
cd talentsync-ai
  1. Install dependencies:
npm install
# or
yarn install
# or
pnpm install
  1. Run the development server:
npm run dev
# or
yarn dev
# or
pnpm dev
  1. Open http://localhost:3000 in your browser

🎭 User Portals

Landing Page

The home page (/) displays three role cards:

  • Candidate Portal
  • College Portal
  • Corporate Portal

Click any card to navigate to the respective dashboard.

Candidate Portal Routes

  • /candidate/dashboard - Overview with stats and job suggestions
  • /candidate/jobs - Job discovery with AI matching
  • /candidate/applications - Application tracking
  • /candidate/career-assistant - AI resume analysis
  • /candidate/aptitude - Aptitude tests (placeholder)
  • /candidate/interview - AI interview (placeholder)
  • /candidate/learning - Learning resources and roadmaps

College Portal Routes

  • /college/dashboard - Placement statistics and overview

Corporate Portal Routes

  • /corporate/dashboard - Hiring funnel and job postings

🎨 Design System

Color Palette

  • Primary: Blue (#3B82F6 to #2563EB) - Trustworthy, professional
  • Secondary: Purple (#8B5CF6 to #7C3AED) - Creative, innovative
  • Accent: Cyan (#06B6D4) - Modern, tech-forward

Gradients

  • gradient-primary: Blue to Purple
  • gradient-secondary: Purple to Pink
  • gradient-accent: Cyan to Blue

Dark Mode

Toggle dark mode using the moon/sun icon in the header. Theme preference persists across sessions.

📊 Mock Data

The application uses realistic mock data for demonstration:

  • 5 job postings (various companies and roles)
  • Sample candidate profile
  • 2 application examples with full timeline
  • Aptitude test questions
  • Career learning roadmaps

Location: lib/data/mock-data.ts

🔮 AI Features (Simulated)

Current version includes AI feature simulations:

  • Resume Scoring: Algorithm-based scoring (completeness, keywords, formatting)
  • Job Matching: Skill overlap calculation
  • Aptitude Tests: Score analytics and recommendations
  • AI Interview: NLP keyword matching (simulated)

For production, integrate:

  • OpenAI API for NLP
  • AWS Rekognition for proctoring
  • Backend API (Django/FastAPI/Node.js)
  • PostgreSQL database

🏗️ Building for Production

npm run build
npm run start

🚀 Deployment

The application can be deployed to:

  • Vercel (recommended for Next.js)
  • Netlify
  • AWS Amplify
  • Any Node.js hosting platform

Deploy to Vercel

  1. Push code to GitHub
  2. Import project in Vercel dashboard
  3. Deploy with default settings

🎯 Future Enhancements

  • Real AI/ML integration
  • Backend API development
  • Database integration (PostgreSQL)
  • Authentication system (JWT + OAuth)
  • WhatsApp/Email notifications
  • Video interview recording
  • Real-time proctoring
  • Payment integration
  • Admin panel
  • Mobile apps

📝 License

This project is created as a demonstration platform.

👤 Author

Built with ❤️ using Antigravity AI


Note: This is a demonstration version with simulated AI features. For production deployment, you'll need to integrate real AI services, backend APIs, and databases as outlined in the implementation plan.

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