As part of my internship at nuSoft, I contributed to the development of a fully functional Hiring Portal designed to simplify the recruitment process for employers. The portal allows companies to post jobs, receive applications, and filter resumes efficiently. I worked on both the frontend and backend, helping build dynamic dashboards, application tracking systems, and resume viewing interfaces. Using the MERN stack (MongoDB, Express, React, Node.js), I developed key components that ensured smooth job posting, applicant management, and communication features. This project gave me hands-on experience in building production-ready features for real-world HR workflows and taught me how to write scalable, maintainable code in a collaborative environment.

I started building Mangochat, a real-time chat application aimed at providing both public and private messaging features. Using React, Node.js, Socket.IO, and MongoDB, I implemented core functionalities such as joining chat rooms, sending and receiving real-time messages, and storing chat history. The UI was designed with Tailwind CSS, and I added features like profanity filtering, user search, and auto-scrolling to improve user experience. Although the project is still a work in progress, it has already helped me gain practical experience with WebSockets, full-stack communication flows, and handling real-time data efficiently. I plan to enhance it further by adding authentication, better chat history management, and group chat support.

I developed a smart, AI-powered Resume Analyzer designed to help recruiters quickly assess and filter candidates. Built using the MERN stack (MongoDB, Express, React, Node.js), the system allows users to upload multiple resumes (PDF/DOCX), which are then parsed, chunked, and analyzed using Gemini AI and HuggingFace embeddings. I implemented a chunked processing system with interval-based automation to ensure scalability when handling large batches of resumes. The app also features a real-time chatbot enhanced with Retrieval-Augmented Generation (RAG) to provide intelligent answers based on uploaded resume content. Additional highlights include Redux-based state management, profanity filtering, personalized preferences and weights for scoring, and a clean, responsive UI built with Tailwind CSS. This project helped me gain deep experience in AI integration, real-world data handling, semantic search, and user-focused design.

I independently built Mangomerce, a full-stack e-commerce website designed to manage and streamline product listings, orders, and customer interactions. The platform features a fully functional cashier dashboard, allowing admins to upload item images, set discounts through dynamic modals, edit product details, and manage stock levels—all built using React, Node.js, and MongoDB. I implemented responsive design using Tailwind CSS and handled secure image uploads with backend API integration. The frontend includes real-time search functionality and intuitive navigation, while the backend ensures efficient data management and order processing. Developing Mangomerce significantly strengthened my skills in full-stack architecture, UI/UX design, state management, and building scalable, real-world web applications.