Every nation is a living network of human connection, populations interacting with their environment, physical infrastructure, and each other to survive. Shaped by conflict, climate, and mass displacement, GraphState models these human systems across scales, from the smallest village to the global scale, to estimate health coverage, infrastructure access, and population flows across millions of unmonitored locations.
Covariate-free at the core. No satellite classifiers. No black-box ML. The network itself is the model. Bring your own geolocated data and we provide the inference engine to make sense of it, at transnational scale, on your infrastructure.
Identify strategic locations for monitoring, reconstruct a full network at a fraction of the cost. By calculating mathematically critical sentinel nodes within the human graph, our inference engine achieves sub-1% error margins, an order of magnitude more accurate than random sampling. Monitor continuously, not once every five years.
Remove any road, facility, or supply corridor from the network and see what cascades. Model mass relocation, catchment failures, and hospital capacity surges before they happen. Conflict-adjusted. Climate-tested. Fragmented humanitarian data streams fused into one operational picture.
Settlement-level health indicators across every country with survey data. Identify coverage gaps between surveys.
Track population flows across disparate humanitarian data sources. Flag coverage numbers that are structurally implausible.
Simulate supply corridor failures. Identify which facilities face cascading capacity surges under climate shocks.
Model disease propagation across settlement networks. Optimize clinical trial site selection, assess vector spread, and map diagnostic test needs.
Stress-test national infrastructure under compound scenarios. Settlement-level vulnerability at continental scale.