HazNetix
HazNetix is building a software-first, hardware-agnostic, AI-assisted hazard intelligence platform for fire service and wildland-urban interface responders. Its implemented Fire 360 workflow organizes simulated incident context—reports, imagery, weather, and location—into an operator-reviewed size-up with approval gates and audit replay. The system is designed so automation advises but never overrides human accountability.
- Government Technology
- Data & Analytics
- Artificial Intelligence
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Fire service and wildland-urban interface (WUI) responders often lack a structured, pre-incident hazard intelligence workflow that integrates a full 360-degree size-up of the fire environment. Fragmented signals across separate tools and timelines, verification delays, and incomplete decision histories can lead to incomplete situational awareness, delayed operational decisions, and increased risk to personnel and communities during rapidly evolving incidents.
Solution
HazNetix is building a software-first, hardware-agnostic, AI-assisted hazard intelligence and response-orchestration platform. Its implemented Fire 360 software organizes simulated incident context—initial reports, imagery, weather, location, and detection records—into a single controlled view for human review, approval, and audit replay. The workflow follows five operational scenes—Detect, Validate, Operator review, Orchestrate, Respond—with every recommended action subject to an explicit human approval gate before it proceeds. The platform uses stable schemas, deterministic fusion, and a normalized event model to create a durable chronological incident record that captures recommendations, approvals, overrides, and state changes. HazNetix is designed around supervised recommendations and staged validation, ensuring that automation does not erase accountability and that operators retain final decision authority.
Target Audience
Primary customers are fire service agencies and wildland-urban interface response teams seeking a structured, operator-reviewed workflow for incident size-up and hazard intelligence, as well as design partners interested in shaping pre-production operational tools.
Features
- Fire 360 size-up workflow that consolidates initial reports, imagery, weather, location context, and simulated detection records into one incident view
- Operator review gates requiring explicit human approval before any recommended action is executed
- Audit replay capability that preserves a chronological incident record with recommendations, approvals, overrides, and state changes
- Normalized event model with stable schemas and deterministic fusion for consistent data organization across incident types
- Hardware-agnostic architecture designed to support open integration paths and adapters, subject to validation and governance
- Staged validation approach distinguishing implemented software (controlled scenarios) from in-development hosted operations and field validation