The AI-backbone of the Future Combat Air System (FCAS) has been made operational, with more than 50 pilots from ten organisations now using the cross-sectional platform, according to a release from Rohde-Scwarzh, one half of the HIS consortium developing the technology, on 29 May 2024.

The AI-backbone was provided by Helsing and Schönhofer Sales and Engineering (a subsidiary of Rohde & Schwarz) just nine months after the contract start in 2023.

According to the release from Rohde-Schwartz, the AI-Backbone offers improvements over the current standards, by introducing standardised procedures across organisations in the military sector and reducing fragmented processes with numerous interfaces.

This centralised platform is also intended to ensure data security and sovereignty for every user and increase flexibility and efficiency across the MiLOps workflow.

“The use of AI will be critical to FCAS air superiority. AI accelerates the evaluation of sensor data, the planning of missions and the use of effectors,” explains Frank Schrudde, managing director of Schönhofer Sales and Engineering. “As an innovative, long-standing partner of the Bundeswehr, we bring vigour to the research landscape. We are proud to have brought the agility of a medium-sized company to the project in collaboration with our partners. We were able to deploy the first demonstrator in an extremely short time of nine months.”

“With the first release, an important milestone in the implementation of the AI-backbone has been reached,” says Stephanie Lingemann, program director and head of the air domain at Helsing. “We are proud to have advanced the AI-backbone from the initial idea to implementation. The development of AI is now being supported in the ongoing phase of the national R&T projects and a decisive cross-sectional contribution is being made to enabling the NGWS.”

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The next stage of development will be part of the second release, expected in November 2024. Rhode-Schwarz intend this update to enable standardised, collaborative AI workflows in highly sensitive environments, and to add additional capability components.