This project involves creating analytical reports and dashboards for retail sales and healthcare metrics. The store sales report tracks sales performance using key metrics such as total sales, targets, and period-based sales comparisons, with filters for date and location. The repair summary report provides insights into repair activities with visual charts and multiple filters. The top sales report highlights salesperson performance, while the top sellers report lists best-selling products. In healthcare, dashboards focus on patient-related metrics, engagement, and group analysis, offering insights into appointments, measures, and patient interactions with various filtering options for effective data analysis and decision-making.

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.

Develop an AI-powered travel platform that integrates real-time travel APIs for flights, hotels, and activities, providing users with personalized itineraries and seamless end-to-end trip booking via a web-based application (future expansion to mobile).