Would appreciate your feedback on something I'm working on.

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Hi I'm Akina from Japan and we develop new SNS named bajji(badge). bajji will visualize reliable relationships. You can connect only with person actually you've met by using our app. And only those who met in person with you can give your assessment to you.By using blockchain, data could be fair to anyone. It keeps service reliability. 1,000 users in Japan and we are trying to expand this service to worldwide as a next step. bajji will solve digital rights on social web. Could you feedback about service for me? Here is my invite URL. If you register from this URL, you and I will get some points only use in this service after authorization... https://bajji.life/en/invite/9WvB-lLkd5M ※web-app(PWA), smartphone only Thank you. Akina

Visit product View on Hacker NewsDec 28, 2019

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

76%76% 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.

TrustMRRFits verified-revenue profile · Strong signals: visualize, users · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

38%38% 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

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: smart · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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