1,000+
Geospatial data points per fire
5
Parallel AI agents
10 min
Data refresh interval
24h
Fire spread forecast
The Problem
Incident commanders synthesize dozens of disconnected sources under extreme time pressure.
When a wildfire ignites, emergency managers must simultaneously track fire behavior, weather, terrain, road conditions, and evacuation status — across fragmented tools, radio channels, and spreadsheets. Every minute of delay compounds risk.
Our Solution
AmberAI unifies all critical wildfire data into a single AI-powered tactical dashboard. Five specialized Claude AI agents analyze fire conditions in parallel — wind, fuel, terrain, hydrology, and community risk — and a supervisor agent synthesizes their outputs into unified 6, 12, and 24-hour spread forecasts, streamed live to the map.
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AI Agent Architecture
Five specialists. One supervisor.
Wind Analysis
Real-time wind speed, direction, and atmospheric instability
Fuel & Weather
Vegetation fuel load, drought index, and humidity conditions
Topography
Slope, aspect, elevation, and terrain channeling effects
Water & Hydrology
Firebreaks, water sources, and drainage patterns
Community Risk
Population density, evacuation routes, and critical infrastructure
Supervisor AgentSynthesizes all specialist outputs into unified fire behavior predictions — streamed via SSE in real time.
Technology Stack
Built for reliability at scale.
Backend
Django
35+ REST APIs
Redis + Celery
SQLite
AI / ML
Claude Sonnet 4
5 Parallel Agents
ThreadPoolExecutor
Structured JSON output
Frontend
MapLibre GL JS
14+ Map Layers
Server-Sent Events
Real-time streaming
Data Sources
FIRMS Satellite
OpenWeather / NWS
OpenStreetMap
OpenRouteService