This thesis presents the conception and development of SpaceM, a comprehensive digital menu solution operating within the WaitHero ecosystem. Designed to address the limitations of earlier implementations, SpaceM introduces persistent user profiling, multi-method authentication, and user-centered customization features, enabling personalized dining experiences for a diverse and growing user base. By capturing individual preferences such as dietary restrictions, allergens, and favorite items, the platform tailors both the interface and the recommendations presented to each customer. A core technical challenge lies in reconciling disparate product data generated by numerous restaurants. To handle this, SpaceM employs a layered relational schema connecting global “master” products with restaurant-specific entries.