I built a macOS app to fix my screenshot chaos (using Local AI)
I am building ScreenSorts because my desktop had become a graveyard of lost information. Like many developers and creatives, I capture dozens of screenshots daily code snippets, design inspiration, and error logs, but I could never find them when I actually needed them. I realized that while taking a screenshot is the fastest way to capture data, it is often the worst way to retrieve it.
I wanted a solution that didn't require manual tagging or drag-and-dropping into folders. I am working on ScreenSorts to build the ultimate automated screenshot manager for macOS that works in the background, so users can stay in their flow state without the digital clutter.
ScreenSorts exists to solve the privacy trade-off in modern productivity tools. We live in the era of AI, but most "smart" tools require you to upload sensitive data to the cloud. ScreenSorts proves that you don't need to sacrifice privacy for power.
By utilizing local, on-device AI and the Apple Neural Engine, ScreenSorts automatically analyzes, tags, and organizes your library 100% offline. It exists to give Mac users a private, native AI workspace that turns static images into a searchable knowledge base, free from monthly cloud subscriptions and data tracking.
As someone building a macOS native AI file manager, I really like how clear your problem framing is, capture is easy, retrieval is hard. ScreenSorts feels like a very natural layer on top of how developers already work.
Congrats on the launch, Nalin! 'Screenshots are the fastest way to capture but the worst way to retrieve' is such a powerful insight. I think every builder has a 'Desktop.png' graveyard.
I really appreciate the privacy-first approach using the Apple Neural Engine. In a world where everything is moving to the cloud, local-first is a massive selling point.
I’m currently building Bossr, a video-first hiring app, and we’ve been debating how much 'AI analysis' we should do on the videos vs. keeping it raw for the 'vibe.'
Question for you: How do you handle the battery/CPU impact of running the Neural Engine in the background? Did you find any specific optimizations that helped keep it lightweight?
This scratches an itch I've had for years. I work with a lot of API documentation and error screenshots, and the number of times I've spent 10 minutes scrolling through a folder of 'Screenshot 2026-02-...' files looking for one specific error trace is embarrassing. The local-only approach is the right move — I'd never install something that ships my terminal screenshots to a third-party server. Smart to lean into the Apple Neural Engine too, keeps the app feeling native rather than bolted-on. One question: does it handle screenshots with mixed content well? Like a browser tab with code AND a sidebar with Slack messages — does it tag both contexts or just pick the dominant one?
The privacy angle is genuinely strong here. Most screenshot tools that add AI search require cloud upload, and for devs who screenshot API keys, internal dashboards, or client data that's a non-starter. Running everything on the Apple Neural Engine is the right call.
Curious about the search accuracy though — how well does the local model handle things like code snippets or terminal output compared to cloud OCR? That seems like it'd be the make-or-break for developer adoption specifically.
Also $500/mo already is solid validation for a single-platform app. Are you planning to stay macOS-only or is Windows on the roadmap?
Great, something similar would come in handy for me too
Love this! Good luck on the launch!
Congratulations on your launch. It looks impressive! What channels are you exploring to attract early users?