AI

AI Reading Companion

Hacker News

AI Reading Companion

hey all - i have been using gpt to read books for about a year now. It's been solid but I wanted: 1. something sleeker, in one app with all the e-reader capabilities 2. something more context aware. i've been hoping kindle would build some ai features, but they're lagging, so i built a ai-powered web e-reader called flow. from the technical side i create semantic embeddings for the entire book as well as analyze it with an llm on upload (key arguments by chapter, historical context etc). i then use basic rag architecture to pass the right data at the right time to power all the features. currently its built for complex non-fiction content, but thinking about making it work well for complex sci-fi / fantasy books. check it out, would love thoughts and feedback.

Visit product View on Hacker NewsMar 27, 2025

Actual performance

4points

1comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: context, using · Missing: mac, agents, macos

91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

AI Native Reading Companion47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI Native Reading Companion

Markee26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

your digital reading companion

Indie Hackers1books

Nara Reading App41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A book reading companion for every kid.

Indie Hackers1ai

Mnemo59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mobile Socratic Reading Companion

Indie Hackers1$100/moai

unix subprocesses for Erlang with reading with backpressure72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

unix subprocesses for Erlang with reading with backpressure

The SQ3R Reading Method28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The SQ3R Reading Method

Footnote30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Reading. Remembered.

Indie Hackers1communication

Resurefy34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Reinvent Reading

Indie Hackers3writing

A privacy first companion AI41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A privacy first companion AI

EverReed65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A personalized reading companion for discovering, tracking,

Indie Hackers1ai

Browse all products Analyze your launch