FindReads
I’ve always felt that most book recommendation engines are shallow, they either use tags or “people also liked” data. I wanted something that actually understands what you mean when you say “slow burn sci-fi with emotional depth” or “books like Harry Potter.” So I built FindReads . It uses GPT to interpret your prompt, queries for books, and returns real titles that fit the vibe. Stack: Next.js, OpenAI API, MongoDB, deployed on Vercel. It’s still a work in progress — the results are surprisingly good for some moods, weird for others, but I’d love feedback from the HN crowd on how you’d…
FindReads launched on October 8, 2025 with 10 votes, #1,488 of 8,178 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
FindReads helps you discover books that match your vibe, mood, or theme. Type anything like “books like Harry Potter” or “sci-fi with emotional depth” and get real titles powered by AI.
Find your next great read with AI. Smart book picks, tailored to you.
Describe what you want to read and get AI‑curated books from top sources. FindReads plans your search, queries top sources (like Google Books & Open Library), and returns a clean list of books with titles, authors, years, covers, and links. Paid users get unlimited searches. Tap the Contact link in the header, or use the feedback widget in the bottom-right corner of the window, send us any question or request and we will get back to you as soon asfrom findreads.app
In the maker’s words, at launch
I’ve always felt that most book recommendation engines are shallow, they either use tags or “people also liked” data. I wanted something that actually understands what you mean when you say “slow burn sci-fi with emotional depth” or “books like Harry Potter.” So I built FindReads . It uses GPT to interpret your…
Does a similar job
all alternatives →- ISI scraped 3B Goodreads reviews to train a better recommendation modelNov 2025 · book.sv · ▲606
Hi everyone, For the past couple months I've been working on a website with two main features: - https://book.sv - put in a list of books and get recommendations on what to read next from a model trained on over a billion reviews - https://book.sv/intersect - put in a list of books and find the users on Goodreads who have read them all (if you don't want to be included in these results, you can opt-out here: https://book.sv/remove-my-data) Technical info available here: https://book.sv/how-it-works Note 1: If you only provide one or two…
Turning books into chatbots with GPT-32023 · konjer.xyz · ▲261So far I've used it to reference ideas from books I've read before. I've also used it to explore books I have not read before by asking the bot questions. Some people have told me they use it like a reading companion. They pause while reading the book if they have a question, and use Konjer to answer it.
I mapped HN's favorite books with GPT-4o2024 · hnbooks.pieterma.es · ▲285Hey HN! I love finding new books to read on here. I wanted to gather the most mentioned books and recreate the serendipity of physical browsing. I scraped 20k comments from HN threads related to reading, extracted the references and opinions using GPT-4o mini, and visualised their embeddings as a map. - OpenAI's embeddings were processed using UMAP and HDBSCAN. A direct 2D projection from the text embeddings didn't yield visually interesting results. Instead, HDBSCAN is first applied on a high-dimensional projection. Those clusters tend to correspond to different genres. The genre…
I made a books recommendation app based on your mood2024 · booksbymood.com · ▲173Hello HN, I noticed that I often looked for new books, depending on my mood (e.g., if I'm feeling tired, I want to find books that'll help me fix that and improve my sleep). So, I created my 1st indie project, BooksByMood. BooksByMood will help you find your next read based on your mood w/ - Books averaging 4.09/5 on Goodreads - Each book comes with an explanation of why it's selected for your mood - 18 moods to explore I hope you'll enjoy using the website, Cheers!
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