The proposed solution is a mobile-first, AI-powered wellness platform designed to empower users to take control of their health through real-time insights, proactive recommendations, and an engaging, gamified user experience. By integrating data from wearables, lab results, medical history, and electronic health records (EHR/EMR), the platform delivers a comprehensive and personalized wellness journey. Advanced AI/ML models analyze this data to offer predictive insights and tailored health guidance, while seamless integration with third-party systems such as LabCorp and Quest Diagnostics ensures a truly connected and data-driven experience.

This project delivers an integrated AI and analytics platform for the Foundation for Sickle Cell Disease Research (FSCDR). It connects ECW (eClinicalWorks) EHR data with advanced AI-based predictive models to identify high-risk patients, automate follow-ups, and streamline state grant reporting (CMO99, CMOAE Tasks 5–13).
The goal is to transform static EHR data into actionable insights — improving research visibility, compliance, and patient outcomes while cutting down manual reporting workloads. The solution supports predictive ER-risk modeling, AI-based outreach automation, and Power BI-driven compliance dashboards across FSCDR’s Centers of Excellence.

AI Powered maternal support Mobile App is being created to ensure that all individuals experiencing the pregnancy journey (no matter what that looks like), are supported mentally and emotionally. This app will serve as a companion for maternity, from the beginning through postpartum. As the pregnancy journey can look and feel different for everyone making it hard to read endless articles, books and take advice from others. Solution is here to help break the stigmas, and leverage AI/ML technology to create a personalized experience just for YOU. App is building a voice-first experience. This is an opportunity to-push the boundaries of voice interaction in a mobile app that truly captures the tone, emotion, and personalization of the end-user.