Health and infrastructure access for the places no survey reaches.
Settlements, the roads between them, and the facilities they can reach — resolved worldwide, and kept current as conflict, climate and displacement move people. Health coverage, infrastructure access and population flow are then measured on that structure.
Request a BriefingCovariate-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.
Deploy as a standalone analytical layer, or seamlessly embed our deterministic engine directly into your existing infrastructure.
Identify strategic locations for monitoring across the full settlement network. Where surveys reach only a sample, the network structure shows what is unobserved — and where new measurement would be most informative. Monitor continuously, not once every five years.
[Request the case study: precision on national health surveys ↗]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.
[Nepal floods, August 2026: open the event analysis ↗]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.