The work proposed focuses on developing AI-based anomaly detection software to detect anomalous signals from quantum sensors used within PNT applications. Infleqtion have been developing a novel approach to AI called “Contextual Machine Learning” which is inspired by quantum contextuality and has been shown to perform particularly well in settings where context can improve the AI model’s decision making, for instance time-series analysis. After system training, Infleqtion will demonstrate the application of the anomaly detection algorithm through direct trials on one of Infleqtion’s quantum sensors, spanning atomic clocks (Tiqker), radiofrequency receivers (Sqywire), or inertial navigation systems (eXaqt). Infleqtion will then conduct both offline and machine-in-the-loop experiments and evaluate the performance of the overall system, with and without the anomaly detection.