Sirens shout. Cawdron speaks precisely.
Site-specific, high-confidence warnings for the streets actually threatened — not area-wide noise for everyone. The civilian alert-precision layer.
How it works
Calm, verifiable, local. The technical detail comes later — trust comes first.
Listen locally
Sensors mounted where the people are — on the poles and rooftops already in your settlement.
Verify before speaking
A single sensor can guess. Several, watching together, can know. Verification comes before any alert.
Warn only who is affected
Not a city-wide siren — a specific, plain-language message to the streets actually threatened.
Built for three audiences
Municipalities
- ▸ Subscription priced inside existing alert-budget lines
- ▸ No civil works, no operator consoles, no training
- ▸ Published per-community performance metrics
Data buyers
- ▸ Ground-truthed, labelled acoustic datasets
- ▸ Controlled-range provenance, documented manifests
- ▸ Licensed access through this portal
Grant partners
- ▸ Civilian-resilience positioning
- ▸ Communities underserved by current alerting
- ▸ Transparent, provenance-tagged reporting
Trust is the product
A warning nobody believes is worse than no warning at all. That is why every community's performance is published — false alerts, misses, response times, uptime — with the provenance of every measurement stated. And every alert that fires gets a plain-language explanation after the fact.
A system that is quiet when nothing is happening is a system people act on instantly when it speaks.
Published per-community metrics
- False alerts per node-week
- Missed detections (loud threat classes)
- Median time-to-alert
- Winter uptime
- Commissioning time
Each metric tagged with its measurement provenance. Dashboard goes live with first pilot results.
Questions
Does this replace sirens?
No. It complements them. Sirens are area-wide by design; Cawdron answers the question sirens cannot: is THIS street, THIS school, THIS hour actually threatened?
What about false alarms?
False alarms destroy trust faster than any threat. Our doctrine is silence-first: a system that mostly says nothing is a system people believe when it speaks. Every alert is reviewed after the fact and explained in plain language.
How do you protect privacy?
The platform is designed privacy-safe. We publish per-community performance metrics — alert counts, response times, uptime — never raw environmental data.
Who is this for?
Communities currently weighing siren-modernization spending, and organizations that need labelled acoustic data for simulation and training.