I built a tool that saves 60% of your time spent reading emails

Hacker News

Hey HN, I am a first-time indie hacker. After working crazy hard on it for around five months, I built a tool that help you to spend less time reading emails. This tool, Summ, summarizes all your emails with suggested actions and delivers them in one email to your inbox at your preferred times automatically. Using Summ you can... 1. Save time: Summ shortens emails by over 60%, saving approximately 50 minutes of your precious time daily. 2. Get action-oriented email summaries: Enabling you to focus only on what requires necessary or immediate actions. 3. With zero distraction: Receive your summaries at times you choose to ensure zero distraction. 4. Reduce stress: Delivers only the information you truly need. Setting up your account takes just a few minutes. The best part is, if you autoforward your emails to your unique, personal Summ email address, all you have to do is enjoy your summaries directly delivered to your inbox, without requiring any further action from you, ever again. I certainly hope that this tool is useful to you as I love how much time it saved me (2314 email summarized, 3412 minutes saved, 89% words removed). I am open to all constructive criticism, and looking forward to hearing about your opinions. Have a wonderful day, Göksu

Visit product View on Hacker NewsJul 30, 2024

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2points

5comments

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Launch Intel predictions

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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.

best fitHighest predicted score across all platforms for this description.

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

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

51%51% 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

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

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

33%33% 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

15%15% 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

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