Dymaxion Labs addresses the growth of informal settlements in Latin America. Using satellite imagery algorithms and cutting edge machine learning techniques, the solution aims to provide (near) real-time monitoring of slums in Latin America. These settlements often do not have critical public services such as sanitation, resulting in health and environmental hazards, especially for children. In addition, data collection through censuses is conducted every 10 years on average – making it difficult to monitor the growth and support needed by communities living in these settlements. Dymaxion Labs’ solution is also useful for rapid response when strong climate events and humanitarian crises occur in risky zones, and could be used to monitor population spread and changes as a result. Over the course of the 12 month investment period, Dymaxion Labs refined the machine learning algorithm to increase accuracy of informal settlement detection and mapping.