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Gallium Defense raises €7.1M to make drone detection cheaper and scalable

Gallium Defense has emerged from stealth with a €7.1 million seed funding round led by Keen Venture Partners and 360 Capital, with participation from Omnes Capital and Polytechnique Ventures. The Fren...

Gallium Defense raises €7.1M to make drone detection cheaper and scalable

Gallium Defense, a French startup founded in 2026, has secured €7.1 million in seed funding to develop a cost-effective and scalable drone detection solution. The GDS-10, a software-defined X-band active electronically scanned array (AESA) radar, can detect FPV drones up to 10 kilometers away with 360-degree horizontal and 90-degree vertical coverage, swarm tracking, jamming resistance, and operation in all weather conditions.

The company's founders are Eric Fournier, Florian Lemoine, and Robin Mandel, all former colleagues from Boston Consulting Group. Fournier, the CEO, and co-founder, brought experience in accelerating complex defense R&D programs. Lemoine, the CTO, previously worked with NATO and France's Directorate General of Armaments (DGA), while Mandel, the COO, had expertise in computing and engineering infrastructure from his time with Thales and Safran.

Gallium Defense partnered with Inovios, a French specialist in high-power radio-frequency technology, to overcome the challenge of developing all components in-house. The founders began experimenting with radar technology as far back as December 2025, leading to the development of the first two GDS-10 prototypes by June 2026.

The company's unique approach involves leveraging existing telecoms technology to make radar systems cheaper. By drawing on commercially available components such as gallium-based antenna elements from 5G telecommunications, Gallium Defense claims to have reduced antenna unit costs by over tenfold. This cost reduction is crucial for making the GDS-10 affordable for critical infrastructure protection and military applications.

Written by urgent.news from Tech.eu's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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