The Food Delivery Application is a comprehensive SaaS-based platform designed to connect customers with restaurants for seamless food ordering and delivery. The application includes three main interfaces:

1. Customer Mobile App: For browsing restaurants, placing orders, and tracking deliveries.
2. Restaurant Admin Web Panel: For managing menus, orders, and restaurant operations.
3. Administrator Web Panel: For overseeing restaurants, customers, orders, and system-wide settings.

The platform supports multi-tenant architecture, enabling scalability for multiple restaurants and customers. It integrates secure payment processing (Stripe), real-time notifications, and advanced order management features.

The project involves developing a mobile application and a web-based admin panel for a platform that allows users to rent personal items. The system supports three key user roles. General users can search, view, and book rental items, make payments, and provide feedback. Item owners can post items for rent, manage their listings and availability, and receive payments. Admin users manage the overall platform including users, item listings, payments, content, and advertisements via the backend panel.
The platform is built using the MEAN stack for the backend and React Native for mobile apps. It integrates with Google Maps, Facebook, Twitter, and payment gateways, and includes SSL encryption for secure transactions. The application supports both Arabic and English languages and offers features such as live chat, push notifications, and social media integration.

The goal of Innoid is to create a centralized, HIPAA-compliant healthcare data warehouse that unifies clinical and operational data from multiple systems. The platform standardizes structured, semi-structured, and unstructured inputs into a single repository, enabling advanced analytics, business intelligence, and AI-powered insights. It directly tackles the challenge of disconnected healthcare data sources, giving organizations the ability to make faster, evidence-based decisions.