Tabletalk: A Smart AI-Powered Framework for Restaurant Recommendation and Reservation

Abstract

TableTalk refers to a new AI-driven mobile app that will simplify the process of restaurant discovery and table booking due to the application of intelligent personalization and user-oriented design principles. The proposed study can help solve the issue of decision fatigue when choosing a restaurant because it incorporates mood-driven AI recommendation systems, as well as a high-quality user interface that is created in Figma. The application applies Design Thinking and User-Centred Design approaches to a high-fidelity prototype with 20+ screens, which has an interactive booking experience of onboarding to confirmation. The system takes into account AI-based filtering by user mood, cuisine likes and dislikes, budgetary limits, travel distance, and any special needs to an excellent extent, which has a great impact on the cognitive load. A considerable amount of usability testing involving more than one user confirmed that the question-based design made the selection faster and more pleasing to the user than the conventional restaurant listing interfaces. The premium aesthetic of the dark theme with gold accents and the standard of accessibility make the theme accessible. The paper introduces the entire design process, the system architecture, the implementation strategy based on the component-based system on Figma, and the quantitative outcomes that prove the usefulness of the AI-integrated UX design to address the issues of artificial dining platforms.

DOI: https://doi.org/10.24321/3117.4809.202510