An offline-first AI eBook reader that runs fully on-device
PageEcho is an offline-first, fully on-device AI eBook reader for iPhone & iPad. Everything runs locally on your device ā TTS, translation, summaries and Q&A, Mind-map. PageEcho supports EPUB, PDF, TXT, MOBI, AZW3, FB2, and shared web articles. It includes offline TTS (Supertonic, Kokoro, Apple TTS), on-device translation, and AI reading tools like chapter summaries, Q&A, and mind-maps. Designed for focused, long-form reading with full offline support. (ā Requires iOS 26+)
Hi Product Hunt š Iām the indie developer behind PageEcho . I built this because I wanted a way to use modern AI (TTS/Translation/others) across everything I read ā books, documents, PDFs, and web articles ā without sending any of that content or my reading habits to a server. Everything in PageEcho runs fully on-device : ā Best-in-class offline text-to-speech powered by modern on-device models (Supertonic & Kokoro) ā Local summaries, Q&A, and AI reading tools ā On-device translation ā N
I think I've tried every iOS TTS app and PageEcho is my new favorite. The voices are excellent, it supports all the types of documents I use (web article, PDF and ePub), has iCloud sync and it works offline, which is very important to me and not supported by most TTS apps. The developer has been very responsive and quick to make enhancements or fixes. I was happy to purchase a Premium license.
I appreciate how PageEcho focuses on clarity and context rather than surface summaries. Being able to understand any page fully with AI while keeping everything on device feels like a meaningful improvement to reading workflows. Well done on shipping this.
Great app! Congrats on the launch š
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.