We participated in the development of a solution for insurance companies that automates the patient management process and helps manage the budget.​ Our goal was to develop a consumer-centric system that could accurately predict medical episodes, improve patient care, and optimize the overall quality and cost of healthcare services provided by insurance companies.

Using AI algorithms, the system accurately foresees medical episodes, encompassing all patient visits for specific health issues, and can predict future occurrences. This predictive mechanism relies on analyzing historical data, encompassing past services, socio-demographic details (such as gender and age), and previous diagnoses.

Additionally, the system incorporates various machine learning models for:

1. Identifying uninsured cases with similar diagnoses.

2. Providing post-discharge support to prevent relapses.

3. Suggesting procedures covered by insurance within two weeks post-discharge.

4. Projecting the patient's well-being after 30, 60, and 90 days.

By integrating these models, the system optimizes patient management in terms of service quality and cost-effectiveness. By leveraging machine learning algorithms and advanced predictive analytics, our consumer-centric AI solution empowers insurance companies to optimize costs, elevate service quality, and provide personalized care to consumers. This innovative approach guarantees tailored care for consumers while enabling insurance companies to make data-driven decisions that enhance consumer satisfaction.