Cornerstone
On-device AI for Apple apps
On-device AI is strongest when the model works close to private user context: finance, health, focus, faith, workouts, notes, and personal workflows.
Short answer
On-device AI runs useful inference on the user's iPhone, iPad, or Mac instead of sending every private prompt or record to a remote model. It is a strong fit when the feature depends on sensitive context, offline use, fast feedback, or a trust promise the product page must be able to defend.
Use local AI for sensitive context
Ledgers, therapy exercises, workouts, tasks, and faith notes are better candidates for local inference than generic public questions.
Use cloud AI deliberately
Heavier models, shared team state, and server automations can justify private cloud AI when the boundary is documented.
Connect AI to product proof
Every product should say what runs locally, what syncs, what is optional, and what never becomes Keelwright data.
Guides in this cluster
On-device AI on iPhone and Mac: what runs locally and why it matters
On-device AI is strongest when the model works close to private user context.
On-device AI vs private cloud AI
The private AI question is not local or cloud. It is which data belongs where.
Private AI apps for finance, health, focus, and personal data
Private AI matters most where the context would be costly, intimate, or embarrassing to leak.