XylemLab

Building a more resilient, data-driven food system by bridging the gap between satellite insights and ground-level action

The Problem

To feed a growing global population, we must produce more food in the next few decades than in the previous centuries, at a time when climate volatility is making our traditional agricultural cycles unpredictable.

Until now, the world’s approach to Earth Observation has been top-heavy. We have access to petabytes of satellite imagery and advanced GEO-AI models, but a critical "last-mile" gap remains. High-level data often fails to reach the hands of those who need it most: the smallholder farmers, local governments, and NGOs making daily decisions on the ground.

Current systems are often standardized for large scale industrial farming. When applied to diverse, smallholder landscapes, these models lose precision. This lack of localized, actionable intelligence creates a cycle of vulnerability, where crop failures are detected only after they occur, and resource allocation remains reactive rather than proactive.