Rapid mapping
Prevent, protect, respond
The Challenge
To respond to emergencies, decision-makers need rapid and accurate geospatial information. But in remote regions, analysts face major obstacles, leading to delays
- It takes hours or days to find, download, clean, and process scattered geospatial data
- Complex and costly traditional tools that require specialized training
- Manual scripts for each use case are hard to maintain, reuse, or audit
- Integrating satellite imagery, population, infrastructure, buildings, weather, and live news or weather data remains a manual process
The Solution
Geospatial AI Agents to query, discover, process and fuse data in real-time
- Merge data such as satellite imagery, terrain, population, roads, buildings inclding real-time weather and news
- Correlate with information from local partners and ground-truth observations to refine AI Agent answers
- Agents delivered maps, impact summaries, and situational reports in-browser, with full traceability and metadata logs
- Designed for ease of use by analysts, program managers, and field teams, no geospatial expertise required
The Results
From analytics to insight, rapid mapping with Geospatial AI Agents turns data overload into clear answers
- Hours, not days, to produce high-resolution risk maps
- Evidence-based targeting of development aid and humanitarian resources
- Greater confidence for planners and decision-makers using transparent, tracable workflows
- Reusable model that can be scaled to other regions, disasters, or development scenarios
The value
Rapid insights
From days to seconds for risk assessments in the browser
Cost-effective
Reduced need for extensive fieldwork and manual data analysis
Data-driven decisions
Support better planning, targeting, and resource allocation across programs
Empowerment
Local teams can conduct their own assessments with minimal training