Infleqtion Secures $2M U.S. Army Contract to Advance Contextual Machine Learning for Assured Navigation and Timing

Key Terms

small business innovation research (sbir) regulatory

Small Business Innovation Research (SBIR) is a government program that provides funding to small companies to develop new and innovative technologies. By supporting these startups, SBIR helps turn ideas into practical products or solutions, which can lead to new markets and growth opportunities. For investors, it signals potential for breakthrough innovations and early-stage growth in emerging industries.

contextual machine learning technical

Contextual machine learning is a form of computer learning that changes its predictions or decisions based on the surrounding information — such as market conditions, patient history, or recent events — rather than treating every situation the same. For investors it matters because these systems can make forecasts and automated actions that better reflect real-world nuances, improving accuracy, reducing surprises, and helping assess risks much like a cook adjusting a recipe to available ingredients and the tastes of guests.

edge-ai technical

Edge-AI is running artificial intelligence tasks directly on local devices — like phones, factory sensors, or cameras — instead of sending data to remote cloud servers. For investors, this matters because it can lower costs, reduce delays, improve privacy, and create demand for specialized chips, software and services, so companies that enable or adopt edge-AI can gain competitive advantages in speed, efficiency and new product opportunities.

gps/gnss technical

GPS/GNSS are networks of satellites and ground stations that tell devices their exact location and provide precise timing, like a digital map and clock in the sky. Investors care because that location and timing data enable and improve countless products and services—shipping, ride-hailing, farming, telecoms and financial trading—and can drive revenue, efficiency gains and regulatory requirements across many industries.

inertial navigation systems technical

Inertial navigation systems are self-contained motion sensors and software that track an object’s position and orientation by measuring its accelerations and rotations, without relying on external signals like GPS. Think of it as counting steps and turns in the dark to know where you are; for investors, these systems matter because they enable reliable navigation in airplanes, ships, drones, and autonomous vehicles, influencing product value, safety claims, and market demand.

boltzmann machine-based models technical

Boltzmann machine-based models are a type of computer learning system that finds patterns by exploring many possible configurations and favoring the simplest, most stable ones—imagine a set of magnets that settle into common arrangements. Investors care because these models can power predictive tools for spotting patterns, anomalies or clusters in large, noisy datasets (like price moves or trading signals), potentially improving forecasts and risk detection, though they can be computationally heavy and hard to interpret.

rf signal processing technical

RF signal processing is the set of technologies that capture, clean up, amplify and transform radio-frequency waves used for wireless communication, radar, satellite links and sensing. Think of it like a kitchen that takes noisy, raw ingredients (radio signals), removes unwanted bits, and prepares a clear, usable dish (data or control signals). For investors, advances or problems in RF processing affect product performance, regulatory compliance, manufacturing cost and competitive advantage in wireless markets.

Phase II SBIR Award Will Expand Use of Infleqtion’s CML in Multi-Sensor Environments to Enhance Resilience Against Adversarial Attacks

BOULDER, Colo.--(BUSINESS WIRE)-- Infleqtion, a global leader in neutral atom-based quantum technology, today announced 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). The 18-month effort will apply Infleqtion’s Contextual Machine Learning (CML) to strengthen the Army’s ability to deliver resilient navigation and timing data in adversarial environments. Infleqtion recently announced plans to go public through a merger with Churchill Capital Corp X (NASDAQ: CCCX).

The award follows Infleqtion’s first-place finish in the xTechScalable AI Challenge, where SAPIENT was selected as one of only four winners from an initial pool of 133 submissions. The contract represents a significant milestone in bringing Infleqtion’s CML technology from concept to application. First introduced at NVIDIA GTC in March, CML allows AI models to learn from diverse data sources and extended timeframes, a key advance toward more adaptive, context-aware intelligence.

“SAPIENT builds on the early promise of CML by applying it to some of the military’s most urgent edge-AI challenges,” said Pranav Gokhale, Chief Technology Officer at Infleqtion. “We’re honored to continue working with the Army to develop scalable solutions that enhance operational resilience in the presence of adversarial threats.”

Contextual AI at the Tactical Edge

Modern battlefield environments require the fusion of multiple streams of data, from GPS/GNSS and inertial navigation systems to computer vision, processed at the edge and often in the absence of stable connectivity. SAPIENT addresses this challenge by combining quantum-inspired multimodal learning techniques and Boltzmann Machine-based models to integrate data from diverse sources, even when some signals are degraded or intentionally spoofed.

The resulting AI is designed to operate on compact, power-efficient edge platforms, allowing for deployment in constrained or disconnected environments.

Validating Feasibility through xTechScalable AI

Infleqtion’s solution was first validated during the Army’s xTechScalable AI competition, held from December 2023 to July 2024, where the company rapidly prototyped and demonstrated its approach to a panel of military, technical, and acquisition experts. The win established the foundation for this Direct-to-Phase II contract, which will fund full system development and testing through October 2026.

This latest award builds on Infleqtion’s growing record of delivering practical innovation at the intersection of quantum technology, artificial intelligence, and high-performance computing. Powered by NVIDIA’s CUDA-Q platform and quantum-inspired algorithms, Infleqtion’s CML enhances AI’s ability to process and adapt to complex, real-time data. The company has already demonstrated early adoption of CML in both Army and Navy programs, including QuIRC, which applies the technology to RF signal processing.

To learn more about Infleqtion’s CML and its applications, visit www.infleqtion.com.

About Infleqtion

Infleqtion is a global leader in neutral-atom quantum technology. We design and build quantum computers, precision sensors, and quantum software for governments, enterprises, and research institutions. Our commercial portfolio includes quantum computers as well as quantum RF systems, quantum clocks, and inertial navigation solutions. Infleqtion is the partner of choice for governments and commercial customers seeking cutting-edge quantum capabilities. Infleqtion announced in September 2025 it plans to go public via a merger with Churchill Capital Corp X (NASDAQ: CCCX). For more information, visit Infleqtion.com or follow Infleqtion on LinkedIn, YouTube, and X.

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Matt Stubbs

Voxus PR

mstubbs@voxuspr.com

Source: Infleqtion