RankPilot AI: Full-Stack JEE Analytics Platform
Budget: ₹1,500 – ₹12,500 INR
Build a full-stack AI-powered JEE mock test analytics platform called “RankPilot AI”.
Tech Stack:
- Next.js 14 + TypeScript + Tailwind + shadcn/ui
- FastAPI (Python)
- PostgreSQL
- OpenAI API
- Recharts for analytics
- JWT authentication
Core Flow:
1. Coaching institute logs in
2. Uploads mock test CSV
3. Backend analyzes student performance
4. AI generates personalized insights
5. Beautiful PDF reports generated
6. Dashboard displays analytics
Main Features:
1. Landing Page
- Modern AI SaaS design
- Hero section
- Features
- Pricing
- CTA
- Dark/light mode
2. Authentication
- Login/signup
- JWT auth
- Role-based access:
- Admin
- Institute
- Student
- Parent
3. CSV Upload System
Accept CSV containing:
- student name
- subject scores
- accuracy
- topic-wise performance
- correct/wrong questions
- time taken
4. Analytics Engine
Calculate:
- accuracy %
- weak topics
- subject strengths
- negative marking ratio
- consistency
- improvement trend
- time management
- burnout/risk indicators
5. AI Insight Engine
Use OpenAI API to generate:
- personalized feedback
- weak topic recommendations
- 7-day improvement plan
- parent summary
- motivational advice
6. Coaching Dashboard
Show:
- total students
- score trends
- weak topics
- batch analytics
- student risk alerts
- charts and heatmaps
7. Student Dashboard
Show:
- performance trends
- AI recommendations
- weak chapters
- rank prediction
- downloadable reports
8. Parent Dashboard
Show:
- student progress
- consistency
- alerts
- AI summary
9. PDF Reports
Generate premium reports containing:
- percentile estimate
- subject analysis
- topic heatmaps
- AI recommendations
- improvement roadmap
10. Database
Create tables for:
- users
- institutes
- students
- mock tests
- analytics
- reports
11. API Routes
Build REST APIs for:
- auth
- CSV upload
- analytics
- AI insights
- report generation
12. UI/UX
Design should feel:
- premium
- futuristic
- AI-first
- clean and modern
Use:
- responsive layouts
- glassmorphism
- subtle animations
13. Code Requirements
- production-ready
- modular architecture
- reusable components
- proper folder structure
- environment variable setup
- README with deployment steps
This is NOT a course platform.
This is an AI-powered student performance intelligence system for coaching institutes.
Tech Stack:
- Next.js 14 + TypeScript + Tailwind + shadcn/ui
- FastAPI (Python)
- PostgreSQL
- OpenAI API
- Recharts for analytics
- JWT authentication
Core Flow:
1. Coaching institute logs in
2. Uploads mock test CSV
3. Backend analyzes student performance
4. AI generates personalized insights
5. Beautiful PDF reports generated
6. Dashboard displays analytics
Main Features:
1. Landing Page
- Modern AI SaaS design
- Hero section
- Features
- Pricing
- CTA
- Dark/light mode
2. Authentication
- Login/signup
- JWT auth
- Role-based access:
- Admin
- Institute
- Student
- Parent
3. CSV Upload System
Accept CSV containing:
- student name
- subject scores
- accuracy
- topic-wise performance
- correct/wrong questions
- time taken
4. Analytics Engine
Calculate:
- accuracy %
- weak topics
- subject strengths
- negative marking ratio
- consistency
- improvement trend
- time management
- burnout/risk indicators
5. AI Insight Engine
Use OpenAI API to generate:
- personalized feedback
- weak topic recommendations
- 7-day improvement plan
- parent summary
- motivational advice
6. Coaching Dashboard
Show:
- total students
- score trends
- weak topics
- batch analytics
- student risk alerts
- charts and heatmaps
7. Student Dashboard
Show:
- performance trends
- AI recommendations
- weak chapters
- rank prediction
- downloadable reports
8. Parent Dashboard
Show:
- student progress
- consistency
- alerts
- AI summary
9. PDF Reports
Generate premium reports containing:
- percentile estimate
- subject analysis
- topic heatmaps
- AI recommendations
- improvement roadmap
10. Database
Create tables for:
- users
- institutes
- students
- mock tests
- analytics
- reports
11. API Routes
Build REST APIs for:
- auth
- CSV upload
- analytics
- AI insights
- report generation
12. UI/UX
Design should feel:
- premium
- futuristic
- AI-first
- clean and modern
Use:
- responsive layouts
- glassmorphism
- subtle animations
13. Code Requirements
- production-ready
- modular architecture
- reusable components
- proper folder structure
- environment variable setup
- README with deployment steps
This is NOT a course platform.
This is an AI-powered student performance intelligence system for coaching institutes.