REEKON CORE unifies wildfire detection signals from every available source — satellites, camera networks, ground sensors, aircraft, and weather stations — distills them with AI, and delivers a clear, actionable picture to the right people before the situation gets ahead of them.
7+
Detection source types
Seconds
Detection to notification
1 tap
From SMS to full intel
Next step
Configure who gets alerted — and for what.
The Alert Profile Builder lets you set up role-based routing by event type, severity, geography, and data source. Right person. Right time. What they actually care about.
REEKON connects to any detection source via API or data feed. Agencies plug in what they already have. No new hardware. No rip-and-replace.
🛰️
GOES-18 / GOES-19
NOAA / OSPO
Live
Last pass: 4 min ago
🔥
FireSat
Earth Fire Alliance
Live
Dedicated wildfire satellite constellation
🛰️
OroraTech
OroraTech GmbH
Live
Thermal infrared constellation
📷
ALERTCalifornia
UC San Diego
Live
1,100+ cameras statewide
🔥
Delphire
Delphire Technologies
Live
Multi-spectral ground sensors
🌡️
Fire Neural Network
FNN — Lightning detection
Live
Lightning strike & ignition prob.
🌬️
RAWS Network
USFS / BLM
Live
Fire weather, continuous
⚡
Utility WX Stations
SCE / PG&E / SDG&E
Live
Interface weather, 1-min
💨
AQMnet / AirNow
EPA / SCAQMD
Live
PM2.5 / smoke particulate
✈️
Aircraft Observer
Air Attack / SEAT
On-call
Manual report intake
🔭
Pano AI Cameras
Pano AI
Live
360° AI-monitored towers
🛰️
VIIRS
NASA / NOAA Suomi NPP
Live
375m active fire detection
📡
Agency-owned sensors
Custom integration
Configurable
Any feed, any format
🚪
CAD / Dispatch
Agency CAD systems
Configurable
Incident feed & unit status
☁️
NWS / Red Flag
NOAA Weather Service
Live
Watches, warnings, SIGMETs
How it works
From signal to situational awareness — fast.
REEKON compresses the gap between a detection event and an informed commander. Every step from signal intake to notification is handled automatically, so personnel are positioned before a fire establishes itself.
1
🛰️
Ingest
All configured detection feeds stream into REEKON simultaneously via API — satellite, sensors, cameras, weather.
Continuous
→
2
🧠
AI triage
Cross-references all signals. Scores ignition confidence, categorizes severity, and surfaces what commanders need to act.
Seconds
→
3
🗺️
Spread model
Physics-based fire behavior projection calculated from wind, slope, fuel type, and moisture. Displayed as a map overlay.
Instant
→
4
📲
Smart notify
Configured personnel receive SMS with digest link and source data. Right people, right threshold, every time.
Automatic
→
5
📡
Escalate
One tap forwards to a wider group — strike team, mutual aid, regional ops. Commander's call, REEKON's speed.
One tap
Live scenario
Watch REEKON work a real ignition event
This reference scenario demonstrates a wildfire ignition event — but the same AI engine handles structure fires, hazmat incidents, community risk trends, and critical infrastructure threats. Watch the confidence score build as each data source corroborates the event.
Ignition confidence0%
Fire Neural NetFireSatALERTCalPano AICAD/911DelphireRAWS
Critical
Thermal anomaly — Verdugo Mountains, LA County
Standby
⚡
Step 1 — Lightning detection
Fire Neural Network registers a 42 kA ground strike at 34.22°N, 118.27°W. Strike energy and fuel moisture index (4%) flag this as high ignition probability. REEKON opens a new incident watch.
Fire Neural NetConfidence: 48%
🌐
Step 2 — Satellite detection
FireSat (Earth Fire Alliance) thermal pass confirms anomaly at the same coordinates. Fire Radiative Power: 847 MW. Brightness temp +38°C above background. Second independent source corroborates the lightning event.
FireSatConfidence: 62%
📷
Step 3 — Camera corroboration
ALERTCalifornia LA-042 confirms visible smoke column matching satellite bearing. Pano AI tower PT-118 detects smoke signature on 360° sweep. Two camera systems, two angles — confidence rising.
ALERTCalPano AIConfidence: 74%
🚪
Step 4 — CAD / 911 report
LA County 911: caller reports visible smoke, vegetation fire, Verdugo Mountains near Burbank. CAD incident #24-08841 created. REEKON ingests the dispatch feed — a fourth independent source now confirms the same location.
CAD/DispatchConfidence: 81%
🔥
Step 5 — Ground sensor confirmation
Delphire node DFN-0441 reports multi-spectral thermal spike — 340% above baseline. Five independent source types now corroborated across satellite, lightning, optical, dispatch, and in-ground sensing.
DelphireConfidence: 89%
🌧
Step 6 — Fire weather context
RAWS VDG-12: NE winds 28 mph gusting 42, RH 8%, temp 97°F, fuel moisture 4%. Red Flag Warning in effect. REEKON scores this as rapid-spread risk: high and triggers the spread projection.
RAWSNWSConfidence: 94%
🗺
Step 7 — Spread projection
Rothermel model inputs: NE 28 mph, slope 18°, chaparral fuel, 4% moisture. Est. 45 acres in 30 min. Physics-based overlay now active on the map below. Toggle it on and off.
Spread model active30-min projection
📲
Step 8 — Notification & escalation
SMS dispatched to Division Chief (Div. A), Regional Ops Center, and IC — Strike Team 7. Commander forwards to wider group with one tap. All parties informed before first engine reaches the scene.
SMS sentEmail sent6 recipients
Live map — Verdugo Mountains
SPREAD PROJECTION
Origin / active
15-min spread
30-min projection
Watch zone
💬
Messages
REEKON CORE
Notification will appear here when the scenario reaches Step 8
