Rhoshield provides an autonomous, self‑learning airspace defense platform that continuously monitors and protects critical infrastructure from hostile drones. Using a multi‑sensor suite and AI‑driven analytics, the system detects, classifies, and autonomously neutralizes threats with directed‑energy, net, or electronic countermeasures, delivering real‑time situational awareness via a secure dashboard.
Funding
Funding not disclosed
Founders
Product
Problem
Critical infrastructure such as energy grids, ports, telecom facilities, and airports faces a security gap because modern drone threats—low‑cost swarms, autonomous strike systems, RF‑silent or fiber‑controlled drones, and pre‑positioned “spider‑web” attacks—can bypass legacy counter‑UAS measures and leave operators with insufficient response time.
Solution
Rhoshield delivers an autonomous, self‑learning airspace defense platform that continuously monitors and protects critical sites from hostile drones. The system integrates multi‑sensor detection, AI‑driven threat classification, and automated neutralization to intercept attacks before they can disrupt operations. By operating independently of human operators, it reduces response latency and eliminates reliance on manual decision‑making. The platform continuously updates its models from real‑world engagements, ensuring adaptability to evolving drone tactics. Results are presented through a secure dashboard that provides operators with situational awareness and compliance reporting.
Target Audience
Primary customers are operators and security managers of critical infrastructure assets—including energy utilities, ports, telecommunications networks, and airports—who must meet heightened protection requirements in a rapidly evolving threat environment.
Features
- Multi‑modal sensor suite (radar, RF, optical, acoustic) for early detection of diverse drone types
- Real‑time AI analytics that classify threats, predict trajectories, and select appropriate counter‑measures
- Autonomous engagement mechanisms (e.g., directed energy, net launchers, electronic disruption) that act without human intervention
- Self‑learning algorithms that ingest engagement data to improve detection and response accuracy over time
- Centralized, encrypted dashboard offering live airspace status, incident logs, and regulatory reporting
- Scalable architecture designed for deployment across energy, maritime, telecom, and aviation sites