Call of Duty

This project aims to develop an AI-powered operational decision support platform to improve the resupply of Ebola diagnostic test kits during an outbreak in the Democratic Republic of Congo (DRC). The platform continuously monitors the operational status of medical clinics, including their available stock of test kits, the number of patients waiting to be tested, and the available nursing staff. Using this information, it automatically identifies clinics that are at risk of running out of testing capacity and recommends the best resupply strategy. The system relies on a Neo4j knowledge graph to model the relationships between clinics and warehouses, allowing an intelligent agent to reason over the logistics network and propose explainable recommendations based on delivery times, available stock, and operational constraints. The objective is not only to detect shortages, but also to support rapid and informed decision-making during an epidemic by identifying the most effective resupply option before a clinic becomes unable to perform testing. This technology could be used for logistic in many different fields. Using neo4j as source of information we ensure that the information are reliable.