Infleqtion has been awarded a $2 million Direct-to-Phase II Small Business Innovation Research (SBIR) contract from the U.S. Army to develop Secured AI for Positioning at the Edge, Navigation, and Timing (SAPIENT). This 18-month effort will utilize Infleqtion’s Contextual Machine Learning (CML) to strengthen the Army’s resilience against adversarial attacks in navigation and timing data delivery. Selected as a winner from an initial pool of 133 submissions in the xTechScalable AI Challenge, SAPIENT combines quantum-inspired multimodal learning and Boltzmann Machine-based models to integrate diverse data sources, even when signals are degraded, for operation on compact edge platforms through October 2026.
Infleqtion’s $2 Million Army Contract for SAPIENT Development
Infleqtion has secured a $2 million Direct-to-Phase II Small Business Innovation Research (SBIR) contract from the U.S. Army to develop SAPIENT—Secured AI for Positioning at the Edge, Navigation, and Timing. This 18-month effort will apply Infleqtion’s Contextual Machine Learning (CML) to strengthen the Army’s ability to deliver resilient navigation and timing data, particularly in environments susceptible to adversarial attacks. The award follows Infleqtion’s first-place finish in the xTechScalable AI Challenge, where SAPIENT was selected from an initial pool of 133 submissions.
SAPIENT addresses the challenges of modern battlefields requiring data fusion from multiple sources—GPS, inertial systems, and computer vision—processed at the edge with potentially unstable connectivity. Infleqtion’s approach combines quantum-inspired multimodal learning techniques and Boltzmann Machine-based models to integrate data even when signals are degraded or spoofed. This AI is designed for compact, power-efficient edge platforms enabling deployment in constrained environments, with full system development and testing scheduled through October 2026.
Infleqtion’s CML, first introduced in March, allows AI models to learn from diverse data sources and extended timeframes. Powered by NVIDIA’s CUDA-Q platform and quantum-inspired algorithms, CML enhances AI’s ability to process and adapt to complex, real-time data. This technology is already being adopted in Army and Navy programs like QuIRC, which applies CML to RF signal processing, and Infleqtion plans to go public via a merger with Churchill Capital Corp X (NASDAQ: CCCX) in September 2025.
Contextual Machine Learning for Tactical Edge Applications
Infleqtion has secured a $2 million U.S. Army contract to advance Contextual Machine Learning (CML) for resilient navigation and timing, specifically through the SAPIENT program. This 18-month effort will focus on applying CML to strengthen the Army’s ability to deliver data in challenging environments. Infleqtion’s CML allows AI models to learn from diverse data sources and extended timeframes, representing a key advancement toward more adaptive, context-aware intelligence—validated by a first-place finish in the xTechScalable AI Challenge from a pool of 133 submissions.
SAPIENT addresses the need for data fusion from multiple sources—like GPS, inertial systems, and computer vision—processed at the edge, even with unreliable connectivity. The system utilizes quantum-inspired multimodal learning techniques and Boltzmann Machine-based models to integrate data, even when signals are degraded or spoofed. This resulting AI is designed for deployment on compact, power-efficient edge platforms, enabling operation in constrained or disconnected environments, with full system development funded through October 2026.
Powered by NVIDIA’s CUDA-Q platform and quantum-inspired algorithms, Infleqtion’s CML is already seeing adoption in both Army and Navy programs, including QuIRC, which applies the technology to RF signal processing. This latest contract builds on a record of delivering innovation at the intersection of quantum technology, artificial intelligence, and high-performance computing and follows plans for Infleqtion to go public via a merger with Churchill Capital Corp X (NASDAQ: CCCX) in September 2025.
SAPIENT builds on the early promise of CML by applying it to some of the military’s most urgent edge-AI challenges.
Pranav Gokhale, Chief Technology Officer at Infleqtion
Validating CML Through xTechScalable AI Competition
Infleqtion secured a $2 million U.S. Army contract to advance its Contextual Machine Learning (CML) technology as part of the SAPIENT program. This Direct-to-Phase II Small Business Innovation Research (SBIR) contract, running through October 2026, will focus on strengthening resilient navigation and timing data in challenging environments. Infleqtion’s CML solution was initially validated through success in the xTechScalable AI Challenge, demonstrating a rapid prototype to military and technical experts, paving the way for this full system development and testing phase.
Infleqtion’s CML approach addresses the need for data fusion from multiple sources – GPS, inertial systems, and computer vision – particularly in environments lacking stable connectivity. The technology combines quantum-inspired multimodal learning techniques and Boltzmann Machine-based models to integrate data even when signals are degraded or spoofed. Powered by NVIDIA’s CUDA-Q platform and quantum-inspired algorithms, CML enhances AI’s adaptability to complex, real-time data, as demonstrated in programs like QuIRC.
The xTechScalable AI competition, held from December 2023 to July 2024, served as initial validation for Infleqtion’s solution. From an initial pool of 133 submissions, SAPIENT was selected as one of only four winners. This win established the foundation for the awarded contract, signifying a key milestone in transitioning Infleqtion’s CML technology from concept to a practical application for the U.S. Army.
