SolarAPIcombines satellite imagery, atmospheric data and ground measurements to generate high-resolution solar irradiance maps. It enables businesses of all sizes to make data-driven decisions for solar project design. In Singapore, GetSolar developed automated rooftop solar evaluations using machine learning to detect slope, obstacles, materials and the surface area is well suited to a machine learning solution because it is a “sharp" question, with timeseries data is already an established use case. renewable energy capacity. Among the countries surveyed by the IEA, around development in mid-2025 were awaiting grid connection. In East Asia, despite ambitious renewable energy targets, permitting similarly remains a major hurdle. with national and local regulations, all while negotiating with local communities. Without effective tools, developers often face fragmented procedures, inconsistent requirements and inter-agency co-ordination challenges, which slow deployment and divert resources from actual project development.