AI-Augmented Event Planning and Task Management Platform: Design, Implementation, and Evaluation

Abstract

This thesis presents the design and implementation of an AI-Augmented Event Planning and Task Management Platform, providing a comprehensive full-stack solution for modern productivity challenges. The system architecture is built using a React.js and Tailwind CSS frontend to deliver a responsive user interface that simplifies the coordination of complex schedules, vendors, and guest lists. This is supported by a modular Node.js and Express.js backend and a PostgreSQL database that utilizes connection pooling for scalable and persistent data storage of all organizational entities. Security is prioritized through multi-provider OAuth 2.0 integration via Passport.js, enabling secure access via Google or GitHub accounts, alongside custom middleware for Role-Based Access Control. The platform is further distinguished by an integrated AI planning assistant component that offers conversational guidance for resource discovery and real-time synchronization for seamless collaborative updates. By incorporating an intelligent recommendation engine to manage budget-based vendor filtering and automated task alerts, the platform transforms traditional planning into a proactive, data-driven experience.