WhisperBot for WhatsApp, read and summarise your voice notes

Hacker News

Hey HN . First post here. Started my journey as a indiehacker in March, challenged myself to make a SAAS in 2 weeks (well, in 1, but it took 2, kinda 'polished it'). The feature exists natively in Telegram for paid users, but it's definitely missing in WhatsApp. So here it is, speech-to-text (w/ Whisper) for your voice notes, + summarisation / translation with ChatGPT. Let me know your thoughts, feedback, etc (kinda struggled for the pricing to be honest, would love to hear from you there). For the curious, the thread where I explain this small journey: https://twitter.com/maelus_/status/1640666512896974849?s=20

Visit product View on Hacker NewsApr 11, 2023

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Did not reach leaderboard

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

83%83% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, chatgpt, notes · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

38%38% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, paid · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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