UploadStudy

UploadStudy

TrustMRR

UploadStudy is an AI flashcard generator for students. Upload a lecture PDF or photos of your notes and get a complete study deck in under a minute, no manual card creation. Study with flip cards in y

UploadStudy is an AI flashcard generator for students. Upload a lecture PDF or photos of your notes and get a complete study deck in under a minute, no manual card creation. Study with flip cards in your browser, manage decks from your dashboard, and buy one-off credit packs when you need more. Free to start, no subscription.

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% 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
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: notes · Missing: mac, agents, macos
18%18% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · 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
12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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