Mosaic ATM is proud to announce that we have been selected for a new U.S. Department of Transportation (DoT) Phase I SBIR award to launch the Fatigue Assessment for Transportation Engineer Determination (FATED) project.
GDPs are sometimes operated inefficiently, resulting in excessive delays. To address this issue, we propose a specific operational technique involving a “Blanket Adjustment” in GDP execution.
The live flight test conducted by Mosaic ATM demonstrated a key concept of Digital Flight, whether a simple set of rules that are independently and simultaneously executed by different flights sharing a common waypoint is sufficient to self-organize in their approach to the waypoint.
Mosaic ATM, a trusted FAA partner in aviation innovation, today announced that this federal directive aligns directly with the mission and capabilities of Mosaic ATM’s EASEL-AI, a next-generation AI-powered platform developed to modernize and automate the UAS waiver evaluation process
Discover how Mosaic ATM’s ARAT tool enhanced TMI parsing accuracy for C90 TRACON, boosting fix closure detection by over 220%. This white paper details parsing logic improvements, regional adaptation strategies, and their integration into the NAS TMI Service to support smarter, more efficient air traffic management nationwide.
Mosaic ATM has been selected as a key subcontractor to CGI Federal on a major Federal Aviation Administration (FAA) initiative to modernize the Notice to Airmen (NOTAM) system—one of the critical components of the National Airspace System (NAS).
Mosaic ATM successfully completed formal testing and validation of ARAT in collaboration with the FAA TFMS test team.
Mosaic ATM is excited to announce the launch of the Performance-Based Flow Management (PBFM) Benchmarking Large Language Model LLM Evaluation project, PBLE. This project aims to evaluate whether artificial intelligence can facilitate the implementation of the PBFM concept and improve Traffic Flow Management (TFM) decision-making.
In this white paper, we explore Mosaic ATM’s air traffic controller communications training tool, the Reconfigurable Interactive Communications Training Environment (RICTE), which leverages artificial intelligence to simulate realistic, multi-modal communication scenarios, enhancing the training effectiveness and proficiency of air traffic controllers.
In this white paper, we explore using large language models and on-premises AI to transcribe and analyze pilot- controller communications, enhancing aviation safety and efficiency through real-time insights and secure, customizable deployment.