53 karma · joined February 14, 2026
It also has the largest gap between AI deployment and AI governance of any sector we looked at.
Three out of four US health systems are running AI in 2026. Less than one in five has governed it. That is not a laggard industry failing to adopt — it is an industry that adopted faster than it figured out what it was doing. The compliance exposure sitting inside most health systems right now is not hypothetical. It is running in production.
We mapped this across financial services, healthcare, energy, manufacturing, and logistics. Healthcare was the one that made us stop.
Full report: https://mobile.wednesday.is/the-enterprise-mobile-ai-report-...
I've documented everything here: https://github.com/alichherawalla/off-grid-mobile-ai/blob/ma...
llama.cpp compiled as a native Android library via the NDK, linked into React Native through a custom JSI bridge. GGUF models loaded straight into memory. On Snapdragon devices we use QNN (Qualcomm Neural Network) for hardware acceleration. OpenCL GPU fallback on everything else. CPU-only as a last resort.
Image gen is Stable Diffusion running on the NPU where available. Vision uses SmolVLM and Qwen3-VL. Voice is on-device Whisper.
The model browser filters by your device's RAM so you never download something your phone can't run. The whole thing is MIT licensed - happy to answer anything about the architecture.
Those changes are not live on the play store / app store but its available on GH. I'll make a release later today.
Let me know what you think!
Only phones with qualcomm chips are able to use the NPU. I'm working towards changing that.
but yeah just to be clear there is no internet needed to run any of this. Infact I'm so averse to it, I've not even added analytics for this one. So flying pretty blind here.
I'm still working on a few things, but let me get a backlog in place and push it so people know what the roadmap looks like
Yeah it wasn't straight forward figuring out the speed + getting it to work for both Android and iOS. Fair bit if complexity. But I'm so happy I got it done.