Hi HN, I built Redactify, a native macOS app that automatically scrubs sensitive personal and financial data, faces, and metadata from documents and images.

The motivation: I frequently use Claude and ChatGPT to analyze invoices and contracts, but I hated the friction of sanitizing them first. I also didn't want to blindly trust the "we don't train on API data" promises of model providers when dealing with actual client data.

How it works under the hood: Redactify flattens the document and permanently destroys the underlying text and EXIF metadata. It runs entirely on-device using Apple's native Vision framework for OCR and CoreML for face detection.

App Store: https://apps.apple.com/app/id6760609039

I'd love to hear your thoughts and wishes on the approach. Also, if you know of any nasty PDF edge cases (weird encodings, hidden layers) I should test against, please let me know!

The possibility to clean your clipboard automatically for LLM Apps (Gemini, ChatGPT, Claude..) is currently in the Appstore review!

Regex and NER both have fun edge cases for redaction. Medical record numbers that look like dates, addresses embedded in prose, account numbers with varying formats. Detection method matters more than people think.