Poles want to defend satellites with microwaves. Contract signed in USA

Poland is making a significant mark in the burgeoning field of space defense with a groundbreaking contract awarded to Wrocław-based startup ARES Shield AI. The company will provide advanced protection for orbital data servers belonging to U.S. firm Lonestar Data Holdings, marking a crucial step in safeguarding critical infrastructure in space.

The contract, valued at over 22 million PLN (approximately $5.5 million USD), will initially protect three satellites, with plans to extend coverage to Lonestar's entire planned constellation. Lonestar is developing the world's first orbital data storage network, StarVault, set to launch commercially in 2027, targeting governments, financial institutions, and critical infrastructure operators.

ARES Shield AI's Sentinel Space Layer platform utilizes a unique non-kinetic approach. Instead of relying on physical projectiles, the system employs high-power microwaves (HPM) combined with advanced artificial intelligence and multi-domain sensor data. This technology can precisely target threats with directed energy beams, neutralizing them without generating harmful space debris, a key advantage over traditional methods.

This deal represents the first time European non-kinetic satellite defense technology has been deployed for a client outside of Europe. Grzegorz Zwoliński, founder of ARES Shield AI, emphasized the immediate need for such protective measures, stating, "Companies moving critical data into orbit today need real protection for their assets, not just declarations and promises of security." The contract validates the market's demand for this innovative technology, positioning Poland as a key player in the global space defense sector.

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Companies moving critical data into orbit today need real protection for their assets, not just declarations and promises of security. The contract with Lonestar confirms that the technology we are developing, HPM, meets a need that the market is already pricing in hard numbers.