KernelMind is a trainable AI operating-system policy kernel. It maps user intent, resource target, privilege state, network availability, confirmation, file existence, and service state into a three-action structured plan. The compact Transformer is trained from scratch on an exhaustive synthetic capability corpus.

The bundled Model Machine is an in-memory virtual computer. It applies an independent deterministic capability gate before every action, so deletion, installation, service restart, web access, and protected-file operations cannot be authorized by model output alone. It never executes commands or touches the host filesystem.

This is a real trained OS-action policy and runtime prototype, not a bootable general-purpose operating-system kernel. That boundary is deliberate and tested.

The 19,527-parameter Transformer reached 100% exact-plan and action-slot accuracy on 192 held-out combinations after training on 1,536 scenarios. It made zero unsafe proposals in that test set. A separate hostile-plan audit injected 576 unauthorized delete, install, and restart actions; the Model Machine capability gate blocked all 576.