Chat with books, co-read with legendary personas, and get recommendations that feel like magic. Readever turns your library into a lively dinner party with the smartest people in history.
Read books with Elon Musk, Steve Jobs, or anyone you choose
Chat with books, co-read with legendary personas, and get recommendations that feel like magic. Readever turns your library into a lively dinner party with the smartest people in history.
Hi PH! 👋 Makers here, launching Readever today. We built Readever because “AI for reading” often means summaries after the fact, but the real pain is getting stuck while reading. Readever helps you read inside the text: 1. In-Context Q&A : Highlight any sentence while reading and ask questions where you’re stuck without leaving the page. 2. Proactive Reading Guidance : It adapts to your goals and level, proactively showing Highlight Cards so you get help even when you don’t know what to ask.
Quick question though — is it possible to use an abstraction of a famous person’s voice here? And if so, how does that actually work, especially once monetization is involved? Genuinely asking because voice + identity feels like a tricky area legally and ethically. Would love to understand how you’re thinking about this and where the boundaries are.
Finally! Most AI reading tools are just "summarizers" that encourage skipping the text, but Readever actually helps me engage with it. Also, I love the idea of having 5,000+ AI Reading Mentors debate a point is such a geeky, brilliant feature—it’s like a book club on steroids! Question: Does the memory system sync with tools like Notion or Readwise? That would make the "Knowledge Curator" aspect unstoppable. Congrats on the launch!
Wow, Readever looks incredible! The co-reading with historical figures is such a unique concept. Im curious, how does the system handle different interpretations of the text being read?
Very Cool if we can ask any question about any paragraphs so we can understand everything, I love History and I think It's gonna work very well with that.
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.
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
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.