Fiolet Hive – crypto payments that you will like

Hacker News

Hello Hackers, I'm Dan from Fiolet. At Fiolet, we focus on web3 recurring payments. You can use Fiolet Hive for: - Subscriptions - Pay-as-you-go - Live Payments It works in 3 simple steps. 1. Users connect their payment methods for recurring charges. 2. Сompanies make invoices according to their pricing models. 3. Fiolet links company requirements with customer's ability to complete a transaction. We allow companies to create value for users without thinking about how to get funds from them. To get started, follow this guide: https://github.com/fioletxyz/api#getting-started We would love to hear your feedback on Fiolet Hive! Please share your thoughts with us in the comments. Thank you!

Visit product View on Hacker NewsAug 19, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, models · Missing: mac, agents, macos

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: recurring, subscription · 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, crypto · Missing: chat, cryptocurrency, make money

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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