Phoenix Fire Labs provides MOCKINGBIRD, an AI‑powered communications engine that listens to tactical VHF radio channels during wildfires, transcribes the audio in real time, and extracts key operational data such as locations, unit identifiers, and incident events. The structured information is automatically pushed to geospatial command dashboards, giving incident commanders an up‑to‑date, map‑centric picture of the fireground and reducing analyst workload.
Funding
Funding not disclosed
Founders
Product
Problem
During wildfire incidents, critical situational updates are often conveyed only through noisy VHF radio chatter and manual logs, creating a delay between field reports and the command center’s view of the incident. This lag hampers timely decision‑making and can increase risk to firefighters and communities.
Solution
Phoenix Fire Labs offers MOCKINGBIRD, an AI‑driven communications engine that listens to tactical VHF radio channels in real time, transcribes the audio, and extracts structured operational data such as locations, unit identifiers, and incident events. The extracted information is automatically synchronized with geospatial command dashboards, providing incident commanders with an up‑to‑date, map‑centric picture of the fireground. By converting voice traffic into actionable intelligence within seconds, the system reduces analyst workload, accelerates resource allocation decisions, and improves overall situational awareness during rapidly evolving wildfires.
Target Audience
Primary users are wildfire incident command teams, fire‑management agencies, and operational analysts who need instant, map‑based intelligence from field radio communications.
Features
- Real‑time speech‑to‑text processing optimized for noisy field audio on tactical VHF frequencies
- Automatic identification of key entities (geographic locations, fire‑unit callsigns, incident events) from transcribed radio traffic
- Seamless push of structured updates into geospatial command interfaces and common operating picture maps
- Continuous monitoring of multiple radio channels to capture all relevant communications during an incident
- Scalable AI architecture that can be deployed on existing command center infrastructure without additional hardware