A military operator interacting with the Hydris system via a rugged laptop positioned on modular transport cases. Image: Project Q
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European firm Project Q is aiming to connect sensors, drones, command-and-control (C2) systems, and effectors into a unified architecture through its new Hydris system.

The platform uses AI to prioritize critical information and coordinate crewed and uncrewed assets across C2 networks and mission systems.

It is built on a Modular Open Systems Architecture, allowing militaries to add new capabilities without redesigning entire systems.

Hydris also uses synthetic data to train AI models and accelerate integration into complex defense environments while separating its open-source framework from protected data and restricted features.

A soldier holding a tactical tablet displaying the Hydris system. Image: Project Q

According to the company, human operators retain final authority over decisions, while automation handles selected functions.

“Rather than replacing existing infrastructure, we integrate what is already in place and connect it into a vendor-agnostic system of systems,” said Leonard Wessendorff, co-chief executive officer and co-founder of Project Q.

“We complement existing military capabilities and support armed forces, security agencies and operators of critical infrastructure in reducing dependencies, regaining digital sovereignty and evolving their own capabilities.”

Built for Flexibility

Built on NATO standards, Hydris is designed to integrate with existing military systems and has already been evaluated in multinational exercises.

The platform runs on containerized hardware within existing infrastructure, enabling organizations to retain control of their data and system operations.

A military operator pointing at a laptop screen displaying the Hydris system. Image: Project Q

Using software development kits, templates, and reference integrations, teams can independently build and configure mission environments.

Once integrated, new capabilities can be deployed across multiple scenarios, reducing engineering effort and speeding the deployment of new technologies.

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