Real-time centimeter-level positioning for satellite-based global navigation
Xona builds space-based navigation infrastructure—GNSS payloads and orbit-determination software for LEO satellite constellations. The tech stack is heavy on FPGA and signal processing (MATLAB, Vivado, Xilinx RFSoC, Verilog) paired with cloud data pipelines (Pulsar, Kubernetes, AWS), indicating a dual engineering challenge: satellite hardware-software co-design and ground-station data scale. Active hiring skews toward mid- and senior-level engineers (54 of 50 roles), with acute pain around manufacturing scale and constellation operations—signals of a company scaling from prototype toward production deployment.
Notable leadership hires: Chief Financial Officer
Xona develops next-generation satellite navigation systems delivering real-time, meter-to-centimeter accuracy globally. The company designs and operates payloads for low-Earth-orbit satellites, coupled with ground infrastructure for signal processing and client-facing positioning services. Their technology stack spans FPGA design (Xilinx), orbit mechanics simulation (MATLAB, Simulink), and cloud-native data pipelines for real-time signal streams. Current project focus includes orbit-determination algorithms, manufacturing scale-up, and a client portal. The organization is engineering-led (68% of open roles) with emerging operations and product teams, reflecting the stage between hardware validation and operational satellite service delivery.
Xona designs GNSS payloads for LEO satellites and orbit-determination software. Their stack combines FPGA design tools (Xilinx Vivado, Verilog), signal processing (MATLAB), and ground-station data pipelines (Pulsar, AWS Kubernetes) to deliver centimeter-level positioning.
Primary pain points center on production scaling: manufacturing efficiency, constellation operations management, orbit insertion/phasing, and collision avoidance. Financial systems and runway management reflect growth-stage pressures.
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Xona's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.