Flash Transcribe
Indie Hackersspeech recognition, speech-to-text, video transcription, ios
I found out there are thousands of audio/video transcribe apps in the App Store, however they are either way too expensive or have a poor transcription engine behind. Therefore I decided to built a clean & simple App
Share cardActual performance
1followers
$120MRR/mo
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps, video · Missing: mobile apps, personal, entrepreneurs55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue33%33% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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