Rethinking book discovery through recommendation systems and UX
A work-in-progress platform combining curated discovery, interaction design, and a proprietary ML recommendation system.
UX/UI
AI Coding
Web App
Database
Currated Feed
Business Strategy
How it works?
When readers rate books, a unique personal profile is created. Every time they ask for a recommendation, Unread analyze at least 20 different "style levers" to choose and rank the top 10 books. It's been benchmarked as 20 times better at predicting what people would enjoy reading next than Gemini 3.1.
For the Data Scientists: Unread proprietary two-stage model uses a Two-Towers retriever paired with a FiBiNET ranker to ensure high-precision matching.
More details soon!
In the meantime: