The Healthcare at Home platform is designed to bridge the gap between patients and healthcare providers by offering a scalable, secure, and AI-powered digital health marketplace. It enables users to book home care services, schedule teleconsultations, receive medical product deliveries, and access personalized health monitoring through a seamless web and mobile interface. By integrating intelligent provider matching, automated scheduling, and escrow-based payments, the platform ensures a convenient, efficient, and trustworthy healthcare experience for patients and caregivers alike.

With an emphasis on accessibility, security, and automation, the platform enhances healthcare delivery by leveraging AI-driven recommendations, HIPAA-compliant data security, and predictive analytics for demand forecasting. Patients benefit from flexible service options, while healthcare providers can efficiently manage their schedules, consultations, and earnings. By offering subscription-based models, commission-based transactions, and promotional opportunities, the platform is not just a healthcare solution but a sustainable business model that fosters long-term engagement and improved patient outcomes.

The nAia AI Fashion Tech Platform aims to revolutionize how users discover, visualize, and shop fashion online by merging artificial intelligence, 3D garment visualization, and e-commerce into one immersive ecosystem.

The MVP (Phase 1) focuses on building a scalable web platform that enables users to:

1. Create personalized 3D avatars
2. Virtually try on garments in real-time
3. Receive AI-powered styling recommendations
4. Shop seamlessly via Shopify Headless Checkout

The ultimate goal is to deliver a personalized, data-driven, and sustainable digital fashion experience, empowering both users and designers. By leveraging AI styling intelligence, 3D visualization, and real-time engagement analytics, nAia bridges the gap between fashion creativity and cutting-edge technology positioning itself as the future of virtual fashion retail.

The project aims to develop a web-based dynamic survey platform designed to capture consumer lifestyle preferences and habits. The survey will consist of four sections with approximately 20 questions and will incorporate conditional logic, ensuring that questions adapt based on user responses. If a respondent selects "yes" to a specific question, additional relevant questions will follow, while a "no" response will allow them to proceed to the next section. The survey should be easily accessible via email invitations or be completed directly by operators, ensuring flexibility in data collection.

The system should support data retrieval, reporting, and potential integration with marketing automation tools, making it a scalable and user-friendly solution for consumer engagement.