Version 1.0.5
Categories:
Version 1.0.5 - Feb 20, 2026
Support Apple Silicon only.
Please review the documentation. Additionally, there is an AI-generated Quality Report. AI is employed to assist in addressing the most technical aspects of RawCull, as I required expertise in extracting thumbnails and JPGs from Sony ARW files during development. RawCull is exclusively developed using default Swift and SwiftUI libraries, and the most stringent concurrency rules are implemented. RawCull incorporates Swift Concurrency and actor isolation, and by setting the most stringent concurrency settings, it is unlikely to encounter any crashes due to data races.
RawCull is also optimized regarding speed and memory for the “heavy” work, which are creating thumbnails and extracting JPGs from Sony ARW files. It easily handles thousands of ARW files. On my MacBook Pro M3 with 18GB of RAM, extracting thumbnails of 2048 x 1365 px for 1100 ARW files is completed in approximately 2 minutes and 30 seconds. All thumbnails are saved to disk cache and also saved in memory for quick allocation. There are more details, in documentation, about caching and how the memory cache works in conjunction with the disk cache to make the culling process as efficient as possible.
RawCull is secure and sandboxed. RawCull is also in the process of being submitted to the Apple App Store.
I do not have any paid subscriptions for AI; instead, I utilize free AI tools when discussing and resolving issues, particularly for the technical aspects mentioned above.