NoamAI provides an AI‑augmented safety platform that fuses radar, ADS‑B, voice communications, flight plans, weather and NOTAM data into a real‑time world model of the airspace. The system predicts conflicts, flags communication errors, and suggests optimal taxi routes, delivering actionable advisories directly within existing ATC and ground‑movement workflows to improve situational awareness and reduce collision risk.
Funding
Funding not disclosed
Founders
Product
Problem
Air traffic controllers and ground operators face cognitive overload due to the sheer volume of flights—over 100 000 scheduled daily—and the complexity of coordinating aircraft movements, leading to communication errors, missed clearances, and a high rate of collision alerts.
Solution
NoamAI delivers an AI‑augmented safety platform that ingests real‑time radar, ADS‑B, voice communications, flight plans, weather, and NOTAM data to generate actionable advisories for controllers and ground crews. The system continuously models the entire airspace (“World Model”) to predict conflicts, flag misreadings, and suggest optimal taxi routes, allowing operators to intervene before errors materialize. By surfacing risk predictions and optimization recommendations directly within existing workflows, NoamAI enhances situational awareness without replacing human decision‑making. The platform is deployable worldwide and integrates with current aviation infrastructure, including ATC consoles and ground‑movement systems. It also extends to contested airspace, providing rapid defensive advisories for high‑value assets.
Target Audience
Primary customers are civil aviation authorities, airline operation centers, and airport ground‑handling teams that manage high‑density traffic, as well as military or defense organizations requiring real‑time airspace risk mitigation.
Features
- Real‑time fusion of radar, ADS‑B, voice comms, flight plans, weather and NOTAMs into a unified airspace model
- AI‑driven conflict detection and risk prediction that alerts controllers to potential collisions before they occur
- Automatic detection of communication errors such as misreadbacks or missed clearances
- Algorithmic taxi‑route optimization to reduce ground congestion, fuel burn and delays
- Predictive safety analytics that identify emerging conflict patterns and suggest mitigations
- Seamless integration with existing ATC and ground‑movement systems via APIs and dashboard overlays
- Defensive orchestration module that generates instant advisory actions for contested or high‑risk airspace scenarios