Music Remote Jam App

Hacker News

I am currently working on a platform that helps musicians connect with each other based on their likes, skills and allow them have fun. Moreover, the platform is meant to allow live jams and turn-by-turn jams. Live jam is just as straight-forward as it sounds: you match with people that would vibe with you and you start jamming with each other while other listen to you. The turn-by-turn jams are meant to validate music ideas on an early stage and help you get inspiration easily from other musician friends or people that could be a match for you. Resulting in a further collaboration for the respective music idea. The person responds back on your small sample with an overlayed sample, and the idea starts to grow and get an outline in a fun way. Tell us what you think: https://docs.google.com/forms/d/e/1FAIpQLScQMxJKD3SBxrHMPxarSZ2OSEauTK_3efLSWcPKYqPm6ncS6Q/viewform?usp=sf_link For more details: http://www.rejam.live/

Visit product View on Hacker NewsAug 28, 2019

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

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

67%67% predicted probability of success on Indie Hackers, 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.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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.

Incorrect prediction on native model

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