Li

Limit – Android content blocker which can't be bypassed

Hacker News

Limit – Android content blocker which can't be bypassed

I've been building Limit, it's an Android app & website blocker that (really!) cannot be bypassed. I'd attempted a bunch of blocking in the past, but kept finding trivial ways to disable the blocking. In the end I built Limit as a blocker I couldn't just disable. It has pre-configured block lists for: - Social media (algorithmic feeds) - Adult content - Gambling Recently we added a 'hands off' mode for parents of ~teens - you can set up the device once, let Limit block social media, but without invading their privacy. More technical explanation: https://limitphone.com/how-it-works

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Actual performance

9points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
48%48% 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
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
22%22% 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
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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