StrikeClimate — Climate Risk Intelligence

StrikeClimate is the climate-tech venture I lead as founder and CTO. This lab track explores the data engine underneath it: ingesting open Earth-observation and weather datasets, normalising them onto a common spatial grid, and producing location-level risk indicators for heat, flooding and rainfall variability. The architecture separates concerns cleanly: a Python ingestion layer schedules dataset pulls, a PostGIS-backed store keeps every observation spatially indexed, and a Django REST API exposes risk summaries by coordinate, administrative boundary or custom polygon. Long-running processing runs on Celery workers so the API stays responsive. Current focus is explainability — every score links back to the source layers and time window that produced it, so a user can see why an area is flagged rather than trusting a black box.