We help governments build and secure the digital capabilities a sovereign state depends on — proven at country scale, under sustained adversarial pressure.
Trusted where failure is not an option
Government systems have to stay secure and operational in high-risk environments, while being severely constrained by compliance demands. We have extensive experience in navigating the overlap between real-world security threats and stringent compliance requirements, in order to deliver practical security posture improvements for critical systems.
Since 2022, our work has been most intensive alongside the Ukrainian Ministry of Defence and its R&D units and leading Ministry-wide cybersecurity programmes.
MINISTRY OF DEFENCE OF UKRAINEThe programme that let the Ministry of Defence of Ukraine assess and mitigate the risks across its defence information and communication systems. Grounded in first-hand understanding of how adversaries operate against defence systems in active conflict.
UNMANNED TRAFFIC MANAGEMENTWith military and civilian drones sharing active conflict airspace, authorities needed a framework to safely integrate UxVs into national airspace — now and post-war. We delivered recommendations tailored to Ukraine's operational realities, creating a foundation for safe drone traffic coordination today and technologically sound regulation tomorrow.
What our partners say
The security engineering team cares not only about security but also about the product itself. It creates real alignment, making security feel like a natural part of the process rather than just a compliance checkbox.
Center of Innovations and Defense Technologies Development of the Ministry of Defence of Ukraine
Cross-domain integration framework for mission-critical systems
Fabric connects heterogeneous battlespace assets and moves data securely to the systems that command and decide — across untrusted networks and under contested, degraded, or disconnected (DDIL) conditions.
Proven in the operational conditions of Ukraine, where both military capabilities and national infrastructure operate daily under real-world attack.
Securing AI from model build to field inference
Deploying AI in defence introduces security problems standard MLOps tooling was never built for: models can be extracted or manipulated, inference queries leak intent, training data carries re-identification risk, and edge accelerators break conventional build pipelines.
Helmet brings together our work on these problems across the AI lifecycle — dataset and training-environment security, security of AI-enabled applications, and protection of models deployed at the edge — used in active conflict, around real threats and operational requirements.
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