Vaulted, Unreleased Music Marketplace

Hacker News

Hello HackerNews, today I've officially launched my new website, Vaulted, which allows musicians and other creators to connect with their most diehard fans. The purpose of Vaulted is to provide a marketplace where musicians can take the demos and unreleased tracks that didn't make it onto any official project, and post them for their audiences to bid-on or buy. The program is written in TypeScript/JavaScript using the SvelteKit framework. The entire front-end and back-end were written by myself, and I plan on working on this pretty extensively for the foreseeable future. Please let me know what you think. And if you have any feature suggestions, or improvements, please let me know and I'll be happy to implement them

Visit product View on Hacker NewsNov 10, 2023

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

84%84% 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

81%81% predicted probability of success on Indie Hackers, 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 released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% 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

12%12% 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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