video1.0<iframe src="https://www.loom.com/embed/8e28cf99e80549e9b95ee977b073a69f" frameborder="0" width="1896" height="1422" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14221896Loomhttps://www.loom.com14221896https://cdn.loom.com/sessions/thumbnails/8e28cf99e80549e9b95ee977b073a69f-7458a4278fc377ca.gif239.802In this presentation, I introduced the Early Warning Analyst project, which aims to identify potential crises by analyzing various data signals that often go unnoticed. By leveraging five virtual agents, we can monitor real-time data and cross-reference it with historical patterns to detect anomalies that may indicate an impending crisis. I demonstrated how the system works using Taiwan as a case study, showcasing features like the constellation map and what-if simulator that enhance our understanding of risk dynamics. I encourage you to explore the results and consider how we can utilize this tool for proactive planning and risk management.