In the digital age, social media platforms have become central to personal and professional networking. However, most existing systems rely heavily on friend-of-friend models or algorithmic trends that often overlook individual interests and personal context. This paper introduces a novel social networking platform that prioritizes meaningful connections through a unique interest-based matching mechanism. The platform allows users to create personalized profiles with bios containing information about their hobbies, passions, or areas of interest. These bios are then analyzed to extract keywords, which are used to suggest connections with other users sharing similar interests. This targeted matching approach enables users to form connections that are not only relevant but also more likely to foster genuine engagement. The system is developed using Python as the primary front-end technology, with MySQL serving as the database backend. Pycharm is utilized as the integrated development environment (IDE), and the platform is designed to run on Windows 10. The architecture is modular, comprising essential user functionalities such as registration, login and recommendation systems, as well as cross-platform support for mobile devices.