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MasterPlan – A complete audio mastering workflow in a plugin

Hacker News

MasterPlan – A complete audio mastering workflow in a plugin

Hi HN, I'm Sam! Long time reader here who finally left a desk job in embedded systems a few years ago to start my own company (Musik Hack) as the technical chops, with my co-founder Stan coming from the music business. It's been really inspiring to read so many stories here, so I'm proud to be going through the motions myself! I'm sharing our first product, Master Plan, an audio plugin for mastering music. We took all the stuff required to turn a decent mix into a major-label quality release and jammed it into one easy-to-digest tool. Then we amped it up with a very special loudness circuit that outperforms some industry standbys and competitors in listening tests. I'm very excited to share and hear what you think, especially if you've got an opinion about how our loudness circuit is doing compared to whatever you're currently using. MasterPlan runs as a VST, AU, or AAX audio plugin on Mac (Intel/Apple Silicon) and Windows. It does require an email address to use, but that's it (no password, 2 factor, or otherwise). ---- PS: If you haven't heard of "mastering," but got this far anyway, it most obviously increases perceived loudness. It also brings out the most pleasing bits of whatever material it started with (like salt does to food). Mastering also helps your track sound good on all sorts of devices, whether they fit in your ear or hang above a stage. Anyway, you've probably seen the word at least once in the phrase "Remixed and Remastered," so now you know!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
92%92% 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, apple, email · Missing: agents, macos, agent
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
50%50% 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
33%33% 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 · Strong signals: audio · 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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