Satellite analysis took months of manual work. AI maps heat islands in hours, letting planners simulate infrastructure impacts.
An environmental intelligence company processing terabytes of Earth Observation data to support urban planning in major European cities.
Satellite data analysis traditionally required specialized data scientists and months of manual work to extract usable insights. This technical...
“AWS provides the scale and processing power we need to transform raw data into actionable insights that drive impactful change in urban and environmental planning.”
AI-driven geospatial insights platform for urban resilience and climate risk analysis.
Cloud computing platform and on-demand infrastructure services.
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Local computers couldn't process millions of satellite images. Parallel ML now maps 50,000+ pollution sources across 1.5M sq miles.
Manual mapping took a year and cost millions. One scientist now completes the work in three days using local AI, saving €1.2M.
Farmers could only react to visible damage. AI now analyzes trap photos and sensors to predict outbreaks weeks in advance.
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
Drowning in 80,000 monthly alerts, analysts struggled to secure data. AI now prioritizes threats, cutting response time by 99%.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.