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Review my startup, Kiddom - made for kids

Hacker News

Review my startup, Kiddom - made for kids

Hey everyone, I would like to tell HN about our startup and our first product, an iPad app. HN has helped me a lot through the ups and downs of making a product and I would really like to get feedback from the HN community. Kiddom is a smart learning environment based on the iPad. It provides an integrated system for parents to download learning apps, assign them to multiple children according to skill, monitor child performance and get some good insights into how well your child is learning Kiddom strikes the right balance between entertainment and education, and helps parents and teachers passively monitor children. Kiddom also provides a single platform for all children in the house, so your 5 year old and 8 year old can be assigned different apps but monitored through one platform. Our games help children to learn through story-telling, games and voiceovers. At launch, we will release 5 different games, where children employ math skills to help the main character, Alan, save his friends. More information is available on our website here: www.kiddom.co

Visit productView on Hacker NewsJan 18, 2013
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% 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: ide, io · Missing: https docs, excited, just released
58%58% 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 HuntOn track for Day 1 leaderboard · Strong signals: apps, single · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, education · Missing: mobile apps, ios, personal
43%43% 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
30%30% 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
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: smart · 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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