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Cipherem – A Self-Sovereign Social Network for Web3 Enthusiasts

Hacker News

Cipherem – A Self-Sovereign Social Network for Web3 Enthusiasts

Hi everyone, my first post on hacker news! I am currently developing, Cipherem, a self-sovereign social network to help web3 enthusiast solve fragmented experience with seamless integrations and we do the heavy liftings instead. I've been to 3 accelerators to refine my business model and was recently accepted into buildspace (which is backed by YC). I would greatly appreciate if you are able to give some feedback, or your experience with my app. Evolving to do list > current affairs at cipherem: fixing bugs (messaging, theme switcher....) Upcoming iterations in cipherem: zk proof login system (say bye to axios + JWT xD) cipherem protocol nft marketplace You can also place your votes or make a new vote under comments on what feature you want to see come alive! Feedbacks are appreciated. Thank you!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
68%68% 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: model, new · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, 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.
TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, io · Missing: https docs, excited, just released
27%27% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: web3 · Missing: chat, crypto, 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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