JEE Guide, AIM ANALYES & ASK

home page
how we help students
get counselling form
dashboard
predictions
mentors
colleges
profile

📖 Project Story: The Journey Behind Three‑Tap

🚀 About the Project

Three‑Tap is a data-driven, student-focused college counseling platform built to help JEE aspirants find the right college and branch based on their rank, preferences, and past admission data. What started as a small idea during my engineering journey has evolved into a full-fledged, AI-supported platform that aims to reduce confusion and bring clarity to thousands of students.

💡 Inspiration

As a JEE aspirant myself, I clearly remember how overwhelming the counseling process was — multiple rounds, shifting cutoffs, incomplete information, and lack of proper guidance. I noticed that most students were relying on outdated PDFs, scattered college websites, and random YouTube videos to make one of the most important decisions of their lives.

That’s when the idea hit me:
What if one platform could bring everything together — data, prediction, guidance — in a clean, interactive way?

I wanted to build a system that was not only powerful and data-rich but also easy enough for a stressed-out student to use in 3 taps or less.

🛠️ How I Built It

The initial version of Three‑Tap was hand-coded from scratch — I designed and developed the frontend, backend, and database structure by myself. Here's a breakdown of the stack and work:

Frontend: React.js, HTML/CSS, basic animations, responsive layout
Backend: Node.js + Express for APIs and business logic
Database: MongoDB for storing cutoffs, colleges, and user sessions
Visualization: Used Three.js and Chart.js for interactive 3D dashboards
Deployment: Hosted on AWS EC2 with domain routing

After building the complete MVP, I realized that user experience and scale were equally important. So, I rebuilt the platform using Loveable AI, which allowed me to:

Improve design consistency
Add smoother animations
Build features visually, faster
Focus more on counseling logic and content

💡 Key Features

🎯 Rank-based College & Branch Prediction
📊 3D Data Visualizations of previous JoSAA rounds
🧠 AI-Powered Chatbot for instant counseling support
📍 Filter by state, quota, category, branch
✨ Clean, mobile-friendly design with smooth transitions

🧠 What I Learned

Building Three‑Tap taught me much more than tech:

How to handle full-stack development independently
How to clean, normalize, and model admission datasets
How to think from a user’s perspective — especially stressed-out students
How to balance feature-richness with simplicity
How to transition from manual dev to no-code/AI-assisted tools like Loveable

It also gave me a better appreciation for UX/UI, deployment, testing, and SEO — things I had never fully explored before.

🧗 Challenges Faced

🔄 Cleaning the messy JoSAA data: Every year, formats changed — needed scripting and deep understanding to normalize.
🧭 Designing for clarity: Avoiding overwhelming visuals while showing complex data took many design iterations.
💬 Building chatbot logic: Training a basic AI counselor that provides helpful, contextual advice was harder than expected.
🌐 Deployment & hosting: Managing servers, SSL certificates, and hosting logic as a student on a budget was tricky.
⌛ Consistency over 1.5 years: Staying motivated and consistent without any external push or recognition.

🎯 Why It Matters

Three‑Tap is more than just a project — it’s a personal response to a broken process I lived through. It’s an effort to help others make better choices. It represents: