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Palantir, Thales, and a startup are competing to build the FAA’s predictive air traffic AI

Posted on April 18, 2026 By 164news66 No Comments on Palantir, Thales, and a startup are competing to build the FAA’s predictive air traffic AI

The FAA’s Predictive Air Traffic AI: Palantir, Thales, and a Startup Compete

April 18, 2026 – 10:38 am

The Federal Aviation Administration (FAA) is developing SMART (Strategic Management of Airspace Routing Trajectories), an advanced AI system designed to extend air traffic conflict prediction from 15 minutes to a remarkable two hours. This ambitious project aims to revolutionize air traffic management, addressing the challenges posed by aging systems and controller overwork, as highlighted by the LaGuardia crash.

Three prominent companies are vying for the contract to build SMART:

  • Palantir Technologies: Boasting strong government connections and impressive revenue growth, Palantir brings expertise in handling vast operational data and presenting it in user-friendly interfaces. Their core business involves developing decision-support tools for governments.

  • Thales: With a long history of supplying air traffic management systems to the FAA and Department of Defense, Thales has an advantage as the current equipment provider for over 99% of instrument landing systems at US airports. Their TopSky platform is already integrated into the aviation infrastructure that SMART will need to utilize.

  • Air Space Intelligence: This Boston-based startup, backed by Andreessen Horowitz, is a smaller competitor but offers significant relevance. Their Flyways AI platform manages over 40% of all US air traffic through partnerships with major airlines, providing them with a strong foundation for this project.

This competition marks a significant step in the FAA’s $32.5 billion modernization program, which involves replacing outdated radar systems and recruiting new controllers. The agency aims to have SMART operational later this year, transforming air traffic management from reactive to predictive.

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