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An Audible alternative for classic audiobooks

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An Audible alternative for classic audiobooks

I spent the last 1yr+ building an audiobook streaming service that focuses on timeless classic works in the public domain. One thing I'm especially proud of is the restoration I did on the "War of the Worlds" 1938 Radio broadcast. I'm really happy with how it turned out. I've made it temporarily free (no login required or anything untoward) to listen to [1] in case anyone is curious. You should compare it with the original [2] and let me know what you think. I find the actual broadcast super engaging and enjoyable. I've done everything from building the app to the audio engineering. A lot of learning involved as my background is on the software side, not marketing, audio engineering, etc. A lot of the initial catalog is stuff that I've sourced from Librivox [3] (legends), but I've done a lot of curation, clean up, editing, mastering, and packaging to make it more enjoyable. There's also some original audiobooks too, and more should be landing each month (they're expensive and time consuming to produce with real humans and AI isn't quite there yet IMHO). It's at a point now where I think it's ready enough to release it to the public. I'd love any constructive feedback (audio quality, UX, concept, etc) that anyone would be willing to provide. Finally, some of the things that are unique: 1) Subscribers vote on what content we produce next (new content monthly is the plan). 2) 3 referrals = a free subscription 3) A "lifetime" option (possibly naive, but it's what I want as a consumer) Anyways, if you even read to this point I appreciate it! [1] https://app.soundreads.io/discover/item/war-of-the-worlds [2] https://archive.org/details/WarOfTheWorlds1938RadioBroadcast... [3] https://librivox.org/

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Indie HackersFits the IH revenue-focused audience · 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: new · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, 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
55%55% 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: month, monthly, way · Missing: mobile apps, ios, personal
42%42% 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
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription, subscribers · 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 · 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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