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Cross-border payments on stablecoin rail

Hacker News

Cross-border payments on stablecoin rail

Hi guys, long time (for years) lurker of HN. I have a product to show you all. We recently launched in beta. Not everyone loves crypto and has diamond hands. Not everyone wants to get paid in crypto. We've built Binamite for users who have clients that pay in crypto (all web3 companies), so that the users can receive money in their local fiat. We do the heavy lifting behind the scenes. Moreover, and more importantly, on the same rails, we make fiat-to-fiat cross-border payments at blockchain speed and cost. That means, for instance, Euro from Europe reaches ZAR in South Africa without ever going through SWIFT. All in a matter of hours. Please check it out if you can. Any feedback is appreciated! PS: Here's the demo for the lazy: https://binamite.com/demo (INR to NGN in 27 minutes). It'd take 3-5 days with SWIFT.

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2points
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% 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.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · 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.
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.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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, paid · Missing: chat, cryptocurrency, make money
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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