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RankWise: Engineering Admissions Predictor & Analytics Terminal

RankWise is a professional, high-precision full-stack prediction engine and comparison suite for engineering admissions under standard entry channels. It analyzes historical cutoff data across JoSAA (IITs, NITs, IIITs, GFTIs) and JAC Delhi (IIIT-Delhi, DTU, NSUT) to advise candidates on safety nets, admission pathways, fee structures, and placement prospects.


🚀 Key Modules & Capabilities

  1. Precision Admissions Predictor: Incorporates dynamic margin windows calibrated per rank bucket (Elite $< 5\text{k}$, High $< 20\text{k}$, and General Mid-ranks) to identify Safe, Target, and Dream admissions.
  2. Interactive Comparison Suite: Direct side-by-side college vs. college evaluation mapping base cutoffs, branch placements, tuition fees, and average CTC levels.
  3. Multi-Year Trend Analytics: D3 and Recharts-powered interactive analytics visualizing cutoff volatility and career prospects.
  4. Autonomous Career Advisor: Generates career forecasts and course advisories integrating modern trends and branch-specific placement metrics.
  5. Fee Calculator: Dynamically adjusts curriculum expenditures based on category concessions, merit waivers, and parental income bounds.

⚙️ Technical Architecture

The application implements a full-stack, single-page application served via an Express server integrated with Vite middleware.

  • Frontend: React 19, Vite, Tailwind CSS, Motion animations (from motion/react), Recharts, Lucide-React.
  • Backend: Express.js with custom ESM/CJS esbuild bundlers optimizing production filesystem footprints.
  • Linter & Static Type Analysis: Strict TypeScript configuration ensuring 100% type-safety and robust null-guards.
  • Storage Layer: IndexedDB & LocalStorage adapters facilitating state consistency for compared lists and customized preferences.

🛠️ Development & Deployment

Required Environment Variable (.env.example)

Ensure you define and specify all environment parameters prior to startup:

# Server Port Configuration
PORT=3000

# Client-side configuration (if needed)
VITE_APP_ENV=production

Installation

Installs base runtime dependencies:

npm install

Direct Development Mode

Boots the Express backend containing Vite-HMR dev servers:

npm run dev

Standalone Production Build

The production build compiles the client-side SPA bundle to /dist, and bundles server.ts into a lightweight, self-contained CommonJS target (dist/server.cjs) using esbuild to optimize Container start performance:

npm run build

Boot Production Container

Runs the compiled commonJS server under Node.js:

npm run start

📊 Directory Structure

├── src/
│   ├── components/            # Isolated view tabs and widget modules
│   │   ├── AdvisorTab.tsx     # Career forecast & advising interface
│   │   ├── AnalyticsTab.tsx   # Visual multi-year analytics reporting
│   │   ├── CollegesTab.tsx    # Interactive catalog listing & details
│   │   ├── CompareTab.tsx     # Dual-entity detail comparison module
│   │   ├── DashboardTab.tsx   # Workspace main console & entry point
│   │   ├── ErrorBoundary.tsx  # Global rendering-interruption safeguard
│   │   ├── PredictorTab.tsx   # Margin-calibrated admissions engine
│   │   └── ...
│   ├── data/                  # Immutable database stores
│   │   ├── collegeData.ts     # Curated campus metadata, fees, and placements
│   │   ├── cutoffHistory.ts   # JoSAA & JAC historical cutoffs dataset
│   │   └── ...
│   ├── types.ts               # Shared global TypeScript definitions
│   └── main.tsx               # SPA React mount point
├── server.ts                  # Production-ready Express & Vite-middleware router
└── vite.config.ts             # Client bundle configurations & Tailwind hooks

📄 License

This repository is distributed under the MIT License. Check the /LICENSE file for details.

About

RankWise – A historical JoSAA admissions analytics and prediction platform built on cutoff records (2021–2025), featuring college prediction, placement analytics, fee estimation, and trend analysis.

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