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Triforce, a free tool to make a multi-sig backup of your seed phrase

Hacker News

Triforce, a free tool to make a multi-sig backup of your seed phrase

There everyone – I'm Mohamed, co-founder of Posterity. We made this after talking to dozens of non-custodial wallets who told us about the issues they had creating a simple backup of their seed phrase. While our focus is on helping families recover crypto after the death of a loved one, we thought we could help with self-recovery as well. Would love to get your thoughts and feedback. Cheers.

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
62%62% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
38%38% 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
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: crypto · Missing: web3, chat, cryptocurrency
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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