ReviewReward uses advanced AI to detect and remove fake online reviews, ensuring authenticity. It features a responsive interface with Next.js and Tailwind CSS, secure user authentication via Google Authentication and Firebase, and stores reviews efficiently in Firebase. Reviews undergo rigorous authenticity checks with machine learning models and Cohere, enhancing trust in user feedback for informed decision-making.

Rashtriya TV is a news blogging website developed by a team of four using Next.js for the frontend and Node.js for the backend. It features an admin panel for easy content management, allowing admins to add, update, or remove news blogs. This project highlights our collaborative skills and expertise in modern web development.

This web application, built with Django, Django REST Framework, and Tailwind CSS, allows administrators to add tasks with points. Users earn points by downloading the app and uploading a screenshot. The project showcases efficient task management and user engagement.

This Python bot is designed to enhance your Discord server by providing a warm welcome to new members. The bot sends a personalized welcome message to users as they join your server, creating a friendly and inviting atmosphere.

E-commerce Flask App is an e-commerce website built with Flask and Tailwind CSS. It features login and signup authentication, purchasing logic, and SQL database management, demonstrating secure authentication and a responsive user interface.

The goal of the Text Review Authenticity Checker project is to develop a system that distinguishes between computer-generated reviews (spam or fake) and genuine user-generated reviews. This model is designed to be beneficial for online platforms and e-commerce websites by filtering out fake reviews and maintaining the credibility of their review systems.