Make your own Bedtimestories using AI

Hacker News

Got excited after seeing this https://news.ycombinator.com/item?id=34514480 this morning. We've been working on a platform for this for the past 3 months. And could not be more excited to share it with you. There is so much in the making, editable stories, image uploads, search in library, Audio, Printed books, Podcast, Magic Photos, talking characters, unlimited images and much more. Let me know what you think. Is personalised content the future of "Kids Entertainment"? Some things we are working on: Magic Photos will let you take you or your kid, and turn them into digital avatars to use in your stories https://twitter.com/LinusEkenstam/status/1617675627695583232 ... Magic Story Cards, will let you create talking characters, that tell the story from their point of view. https://twitter.com/LinusEkenstam/status/1615715273432080388 Extremely excited about what we are building. Now Ask me Anything!

Visit product View on Hacker NewsJan 25, 2023

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

86%86% 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.

Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist

80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos

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

TrustMRRLess likely to generate early MRR · Strong signals: personal, month · Missing: mobile apps, ios, entrepreneurs

49%49% 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

44%44% 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 · Strong signals: audio · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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