The Architecture of On-Device Privacy — How Swipe Cleaner Keeps Your Photos Local

Short summary

Swipe Cleaner processes photos entirely on-device using iOS Core ML rather than uploading to servers, making privacy an architectural guarantee instead of a policy promise. This requires aggressive model compression and careful memory management but eliminates cloud infrastructure and usage analytics. The author argues privacy-first architecture incurs engineering costs but is increasingly important as the AI industry defaults to data collection.

• •On-device ML using Core ML and Neural Engine eliminates photo uploads to servers
• •Requires technical trade-offs: slower model updates, no usage analytics, variable device performance
• •Privacy becomes an architectural property of the system, not a company promise

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