Projects using ChatGPT in PuneProjects using ChatGPT in PuneBookNWatch
Overview
BookNWatch is a full-stack movie ticket booking platform built using the MERN stack. The application enables users to explore movies, select seats in real time, complete secure online payments, and receive automated booking confirmations. The platform also includes administrative controls for managing movies, shows, bookings, and users.
Problem
Online ticket booking systems must handle concurrent seat selection, secure payment processing, booking confirmations, and automated seat management without creating conflicts or double bookings.
Solution
I developed BookNWatch to provide a seamless movie ticket booking experience with real-time seat selection, secure Stripe payments, automated booking workflows, and reliable seat management through background job processing.
Features
Movie Discovery & Show Listings
Real-Time Seat Selection
Seat Locking System
Secure Stripe Payments
Booking Confirmation Emails
Automated Booking Expiry
Clerk Authentication
Protected Routes
Admin Dashboard
Responsive User Interface
Technical Implementation
Frontend
React.js
Context API
Backend
Node.js
Express.js
Database
MongoDB
Mongoose
Authentication
Clerk Authentication
Payments
Stripe
Stripe Webhooks
Background Processing
Inngest
Email Services
Nodemailer
Key Highlights
Server-side seat locking prevents double booking
Automated booking expiration after inactivity
Stripe webhook-based payment verification
Background job processing using Inngest
Automated email notifications and confirmations
Secure authentication and authorization
Scalable REST API architecture
Full administrative control panel
Tools & Technologies
Frontend
React.js
Context API
Axios
Backend
Node.js
Express.js
Database
MongoDB
Mongoose
Authentication & Payments
Clerk
Stripe
Stripe Webhooks
Automation & Communication
Inngest
Nodemailer
Development & Deployment
Git
GitHub
Postman
Vercel
Live Project
https://book-n-watch-mu.vercel.app
Source Code
https://github.com/sahilnikalje/BookNWatch BharatGo is a no-code e-commerce platform built for small business owners across India — many of them first-time digital sellers with no technical background. When I joined, their onboarding flow was an 8-step process with no guidance, no progress feedback, and no sense of what the end result would look like. Drop-off was high and the support team was flooded with setup questions.
I led the full redesign end-to-end: user research, flow restructuring, UI design, and iteration with the engineering team across a 2.5-month sprint.
The core insight was that merchants weren't abandoning because the product was bad — they were abandoning because they couldn't visualise what they were building. So I restructured the flow into 5 progressive stages and introduced a live store preview that updated in real time as they filled in details. Every decision was about reducing cognitive load and building confidence at each step, not just reducing the number of steps.
The result: onboarding completion time dropped 40%, drop-off reduced by 35%, first-week engagement rose 28%, and onboarding-related support tickets fell by 30%.
The visual language was kept deliberately simple — clean cards, strong progress indicators, friendly microcopy — because the product needed to feel approachable to non-technical users, not impressive to designers. 
