It is an in-venue restaurant ordering system that allows customers to pre-order food for on-table delivery or pickup, eliminating the need to wait in long queues. The system will consist of a mobile application for customers and a web-based backend for restaurant management.

An AI-first, Gen Z–oriented fashion styling app enabling users to upload wardrobe items, receive personalized outfit suggestions using AI, and engage socially via outfit polls and feeds. The solution leverages Firebase’s scalable cloud backend and integrates OpenAI for prompt-based outfit generation. Users can manage a virtual closet, receive AI alerts on missing wardrobe items, and interact with a community through polls and comments. It also includes an admin panel for moderation, analytics, and subscription management. Monetization is driven through subscription tiers and integrated ads. The product is designed as a progressive MVP with clearly defined “must-have” and “nice-to-have” features to facilitate phased rollout. Post-launch, the client aims to validate market fit and scale with affiliate shopping and influencer integrations.

The application is designed for the Saudi Arabia healthcare market, enabling patients to access remote consultations via video/audio calls with therapists and specialists. It includes features like pharmacy and laboratory modules, delivery management, and sample collection. The application will be HIPAA compliant, ensuring patient data security and privacy.