Scaleout CEO: battlefield AI must run disconnected, not rely on central data centers

September 6, 2026 at 03:30 PM2 min

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Scaleout CEO Andreas Hellander says battlefield AI must keep functioning when communications fail, as the US military pushes AI into every arm. He argues that traditional data centers are vulnerable to cheap missile strikes, citing Iran's lessons in the Strait of Hormuz. The company's architecture lets disconnected nodes run local inference and cache data until links return.

Key Facts

Scaleout CEO Andreas Hellander holds a PhD in Scientific Computing and is an Associate Professor at Uppsala University.
Palantir has begun deploying shipping containers filled with Nvidia hardware as an alternative to traditional data centers.
Scaleout has worked with NATO, most recently the Swedish Air Force, and defense primes such as BAE Systems.
In Scaleout's architecture, a disconnected node continues local inference using its last approved model, caching detections and telemetry until a link returns.

Vulnerability of Centralized Data Centers

Traditional data centers in the Middle East have already shown their weaknesses, as sprawling warehouses make easy targets for cheap missiles. A single hit can take entire systems offline, seriously damaging an army's capacity to function. The conflict circling the Strait of Hormuz is providing valuable lessons for warfighters, according to Hellander.

Decentralized Compute and Federated Learning

Palantir has already begun deploying shipping containers filled with Nvidia hardware as an alternative to the traditional data center. These containers can be deployed on frontlines and connect directly into operational workflows, offering decentralized compute where it is needed most. Scaleout builds infrastructure for edge AI and federated learning that trains models on distributed, sensitive data without centralising it. The company has worked with NATO, most recently the Swedish Air Force, and defense primes such as BAE Systems.

Resilience Through Disconnected Operation

The aim is not to promise an unbreakable connection; it is to stop the loss of one component from taking down the whole capability. In Scaleout's architecture, a disconnected node continues local inference using its last approved model, caching detections and telemetry until a link returns. Multiple aggregation points can be used above the edge, and if one becomes unavailable, clients can be reassigned and training can proceed with those still reachable.