Case Studies
Real deployments. Measurable results.
Each engagement below is a full deployment — from data ingestion to live operations. No demos, no proofs of concept.
Faraja: Crowdsourced Crisis Damage Assessment
UNDP's RAPIDA methodology delivers early recovery insight from satellite imagery, night-light data, and social media — but ground-level, structured field data still takes days to arrive. Kairos Spatial Solutions built Faraja to close that gap: an open-source, end-to-end platform that lets communities submit geolocated, AI-triaged damage reports over a mobile app or WhatsApp within 72 hours of a sudden-onset disaster, in all six official UN languages, fully offline-capable.
- 90.2% AI damage-severity accuracy (MEDIC-trained)
- 500,000+ report capacity per crisis
- All 6 UN languages, including RTL Arabic
- Mobile PWA + WhatsApp — zero app install
Gold Prospectivity Mapping, Kakamega County
Machine learning targeting across the Busia-Kakamega Greenstone Belt. Two independent models were trained on 61 predictor layers and 68 confirmed gold occurrences, then validated on ground the models had never seen, to rank where exploration should look first.
- 61 predictor layers across four data streams
- 0.981 ranking score on held-out ground
- Zero of 68 known occurrences missed
- 226.5 km² ranked high priority
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