Projects Built
Placement ERP
Built a full-stack dashboard platform with user roles for students, faculty, and placement officers. Helped streamline placement data access and reporting across departments.
Interactive Resume Chatbot
Built an AI-powered resume chatbot using Python, OpenAI API, and Gradio that enables interactive conversations about professional experience.
MCP Excel Server
Built a TypeScript-based Model Context Protocol (MCP) server that provides read-only access to Excel (.xlsx) files using ExcelJS, enabling AI assistants to interact with spreadsheet data through standardized tools.
Messaging Web App
Built a real-time messaging application using React and Socket.io for instant communication. Users create unique IDs to connect with friends and exchange messages seamlessly. Features contact management system for easy friend connections. Deployed with backend on Heroku and frontend on Netlify for full-stack cloud hosting.
Employee Attrition Detection App
Built a React/Node.js web app with ML.js to predict employee turnover risk. Trained on employee datasets to provide individual and company-wide attrition predictions. Features real-time dashboards helping HR teams make data-driven retention decisions.
Restaurant Billing & Analytics App
A full-stack MERN app deployed on Vercel for restaurant owners to manage orders, billing, and sales analytics. It features real-time order tracking, a centralized dashboard for daily sales, and integrated data insights to identify trends. Built with a modern, responsive frontend and a scalable backend, it demonstrates practical use of the MERN stack in a real business context.
Bookify
Bookify is a web app where you can search any book add the book to your reading list comment down about books and read them. Used React.js and Tailwind CSS where users can search books, add them to reading lists, and engage through comments. Features AWS backend with DynamoDB for data storage, Cognito for authentication, and GraphQL APIs.
FloraHunt - AI Flower Identification iOS App
Built a native iOS application using Swift and Core ML that identifies flower species through camera capture. Leverages the Oxford 102 category flower dataset to recognize and classify flowers in real-time. Features machine learning integration for accurate botanical identification, helping users discover and learn about different flower varieties through their mobile device.