I
I made an app to take highlights easily from PDF books
Hacker NewsI made an app to take highlights easily from PDF books
Share cardActual performance
3points
3comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto70%70% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting19%19% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos19%19% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
SummIt27%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
AI annotates your PDF with summaries and highlights
Product Hunt+8An
An app that recommends books on your preferences36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
An app that recommends books on your preferences
Hacker News2Ju
Jupyter kernel that highlights cells with references to stale data57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Jupyter kernel that highlights cells with references to stale data
Hacker News3Bu
Build An App That Books Vacations To The Moon57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Build An App That Books Vacations To The Moon
Hacker News1Bo
BookNomads – borrow or lend books around you55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
BookNomads – borrow or lend books around you
Hacker News2Bu
Bubblin – Bandcamp for books55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Bubblin – Bandcamp for books
Hacker News2Bu
Bubblin – Bandcamp for books55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Bubblin – Bandcamp for books
Hacker News138A
A RottenTomatoes for Books55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A RottenTomatoes for Books
Hacker News146Bo
Books for Programmers66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Books for Programmers
Hacker News1St
StumbleUpon for books55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
StumbleUpon for books
Hacker News37