This direction feels especially relevant for enterprise use cases. On-device AI avoids cloud latency and subscription costs, but enterprises also gain privacy, compliance, and real-time responsiveness when models—and sensitive data—stay fully local. It’s compelling to see this shift: not just a fallback for poor connectivity, but a strategic architecture choice where endpoint control (encrypted storage, NPUs, hardware trust) is as critical as algorithmic capability. Great post!