NoamAI
NoamAI, a Boston company led by co-founder Luke Gotszling, is developing an AI assistant for air traffic controllers in the tower.
Unveiled at Airspace World in May 2025, the patent-pending system is designed to predict conflicts, parse controllers' radio calls and draw on radar, transponder and surface surveillance, with drones and eVTOL aircraft on its roadmap. It has not yet been deployed and no customers are named. Its funding is listed as an 8 million US dollar Series A but is not confirmed.
No verified deployments yet
NoamAI is profiled in the companies register, but no deployment has been verified against published evidence. Records are added as evidence is reviewed and graded.
Products & Solutions
1 productAI Air Traffic Controller
A patent-pending AI-powered decision-support system for air traffic control towers that processes real-time multi-source data, including radar, ADS-B, voice communications, flight plans, weather, and NOTAMs, to provide controllers with enhanced situational awareness, predictive conflict detection, and ground movement optimization.
Air traffic controllers face cognitive overload, communication errors (incorrect readbacks, misheard directives), and ground congestion due to legacy infrastructure unable to keep pace with modern airspace demands. The system provides AI-augmented monitoring and predictive alerts to reduce human error and workload during peak traffic periods.
- Real-time multi-source data integration, continuously evaluates radar, transponder, and voice data streams
- Augmented ATC, intelligent monitoring of communication channels to flag miscommunications and readback errors
- Predictive conflict detection, identifies potential hazard scenarios, including at smaller airports lacking surface surveillance
- Optimized ground movement, algorithmic management of taxi routing to reduce congestion, fuel burn, and delays
3 more features
- Human-AI interface, designed for collaborative operation between AI system and human controllers
- Increased airspace capacity, supports accommodation of eVTOL and drone operations
- Defensive Orchestration mode, same World Model engine adapted for protection of high-value assets in contested airspace
Technical specifications (6)
- Machine learning algorithms and predictive modelling for real-time data analysis
- Processes thousands of data points per second
- Inputs: Radar, ADS-B, voice communications, flight plans, weather data, NOTAMs
- Outputs: Conflict resolution advisories, risk predictions, taxi optimization recommendations
- Natural language processing for voice communications parsing and standardized format articulation
- Patent-pending (as of May 2025)
Profile data from the Aerostack companies register; deployment records from the verified register. Evidence grades: T1 first-party confirmation, T2 credible reporting. See Our approach for how records are graded.