Endel – sound environments to help you focus

Hacker News

Hey, Hackernews! We are working on a technology to help you focus. Endel generates personalized sound environments to help you focus faster, stay in the zone for longer periods of time and relax better. It's an evolved procedural version of everyone's favorite Music for Programming podcast. We are currently going through Techstars Music program in LA and we need your help. We have created a web prototype of Endel that works in the browser. Can you please test it during one of your deep work sessions and provide feedback? There's also an iOS version available by request. Please visit https://work.endel.io and see if it's working for you!

Visit product View on Hacker NewsApr 9, 2018

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

74%74% 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: new · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, personal · Missing: mobile apps, entrepreneurs, apps

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

52%52% 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

34%34% predicted probability of success on AppSumo, 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.

Correct prediction on native model

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