Three Products. Three Problems Solved. Three Lessons Learned.

Below are three full-stack applications I've shipped — each demonstrates a different aspect of MERN development, from brand experiences to e-commerce to AI-powered tools. Every project is live and interactive. Click through to see the work.

Nitin Patyal full-stack MERN projects showcase - Dr Pepper, UrbanKicks, BugPredict AI applications
Brand Website

Dr Pepper

Drink Company

The Challenge

Create an immersive brand experience that showcases product range and engages users through interactive, visually compelling storytelling.

The Solution

Built a React-powered brand site with scroll-driven animations, interactive product filtering, and dynamic content pulled from a REST API backend. Every interaction reinforces the brand while maintaining performance.

Key Features

  • Scroll-driven animated product reveal sections
  • Interactive flavor catalogue with real-time filtering
  • REST API integration for dynamic content management
  • Responsive design optimized across all devices

Tech Stack

React.js Node.js CSS3 MongoDB REST API Animations

Project Scope

Frontend Framework React.js
Backend API Node.js
Database MongoDB
Status Live

Outcome

A fully functional, production-ready brand site that combines visual storytelling with technical precision. The scroll-driven interactions create memorable user experiences while the API integration allows for easy content updates. Demonstrates expertise in modern React patterns, CSS animations, and full-stack architecture.

UrbanKicks

E-Commerce — Sneaker Store

Problem

Build a full-featured e-commerce platform with secure user authentication and admin capabilities that scales with real sneaker culture.

Solution

JWT-secured authentication, dynamic product catalogue with search and sorting, complete cart, wishlist, and admin panel flows. Every feature built with production-ready security and user experience in mind.

Technologies

React.js Express.js JWT MongoDB

Key Features

  • JWT-secured user authentication & session management
  • Dynamic product catalogue with search & sorting
  • Full cart, wishlist, & admin panel flow

BugPredict AI

AI Tool — Developer Productivity

Problem

Create an AI-powered bug detection system that predicts issues before they ship.

Solution

ML-powered static analysis with risk probability scoring, real-time dashboard with heatmaps, REST API supporting multi-language input.

Technologies

Machine Learning Node.js FastAPI MongoDB

Key Features

  • ML-powered static analysis with risk probability scoring
  • Real-time bug prediction dashboard with heatmaps
  • REST API architecture supporting multi-language input

Why This Matters

BugPredict AI demonstrates advanced backend capability and AI/ML integration — skills that differentiate from typical junior developers. This project bridges traditional web development with machine learning, showing ability to architect complex, intelligent systems.