OxRad

Insights

On-device vs cloud radiology AI: where your data goes

The architectural choice behind every radiology AI tool, and why it decides your privacy posture before any model runs.

Every radiology AI product makes one decision before it reads a single scan: where inference runs. Cloud tools send the study off-site to the vendor’s servers. On-device tools keep it in the building. That single choice sets the privacy posture for everything that follows.

The transfer itself is the largest risk. The moment a study leaves your network for inference, the attack surface widens: it transits the public internet, lands on infrastructure you do not control, and is often retained there. Keeping inference on-device removes that transfer entirely, instead of defending it in flight.

The choice also decides data residency and cost. On-device, residency is wherever your hardware sits, which keeps data-protection decisions in your hands; there is no per-study cloud inference dependency and no reliance on connectivity. And it changes nothing about clinical responsibility: with OxRad, the on-device draft is reviewed, edited, and signed by a qualified radiologist on every study.

For the short version, see why on-premise matters for radiology.

Evaluate on-site AI reporting that keeps patient data on your premises.

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