I Built Presync.io – A macOS Music Production Tools AppStore

Hacker News

Hey HN, I built Presync.io to simplify plugin management for music producers on macOS. Presync lets you easily discover, install, and manage music production plugins. Read it as "Steam for music production software". What it has now: - One-Click Installation - 110+ Free Plugins - Video Reviews and Tutorials for plugins (in progress) - Management Stuff: delete for any plugin in your system, MVP of updates (very early stage) Backstory: I love music production and development. This past spring, I started Presync to move away from the endless methods of reading/writing PDFs and Excel files. Initially, I didn't have much time to dedicate to it. This spring, I burned out on my main job (Excel and PDFs are now my child trauma) and decided to focus on Presync. I found a guy to help with content (which I dislike doing), and we've been making great progress. Thank God I'm a fullstack guy so I can do everything myself. I'm using: - Backend: Django (planning to switch to TS + tRPC + Prisma) - Electron (maybe tauri later, not sure) - React + TS + Tailwind on the frontend Plans: - Community features: comments, reviews, and ratings - More plugins and software - Presets - Skins? I’d love to hear your thoughts and experiences to help make Presync better. Try it out and let me know if you have any questions or run into any issues. Best, Max

Visit product View on Hacker NewsAug 15, 2024

Share card

Actual performance

7points

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

96%96% 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: mac, macos, apps · Missing: agents, agent, cursor

87%87% predicted probability of success on Product Hunt, 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

46%46% 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 · Strong signals: apps, video, way · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

13%13% 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

Similar products

Next music production by communicating with AI38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Next music production by communicating with AI

Hacker News5

ListenBrainz macOS Scrobbler for Music.app38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ListenBrainz macOS Scrobbler for Music.app

Hacker News2

Producr54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Music Production Service

Indie Hackerscommitment-side-project

GitBrand.io72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

NextJs Tools to take the app from development to production

Indie Hackers1$100/moai

muted.io45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

interactive tools and references for music theory

Indie Hackers

Blunders.io, a tool to profile JVMs in production60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Blunders.io, a tool to profile JVMs in production

Hacker News46

StackImpact – Java Production Profiler57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

StackImpact – Java Production Profiler

Hacker News1

POC AES implementation in C (not for production)25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

POC AES implementation in C (not for production)

Hacker News1

We ran a sycophancy experiment on Claude and built a music publication56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

We ran a sycophancy experiment on Claude and built a music publication

Hacker News1

LambdaNews.io, an HN client built with Vue65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LambdaNews.io, an HN client built with Vue

Hacker News9

Browse all products Analyze your launch