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A FOSS Expense Splitter

Hacker News

A FOSS Expense Splitter

Hey! Showing off a project I've been working on for a while. Peanut Split is an expense splitter where the room is a link. There are no accounts; people just join via the link. Source: https://github.com/peanutprotocol/peanutsplit (AGPL-3.0). One fun bit is that not only are 162 currencies supported, but you can also add any imaginary currency; gold doubloons, friendpoints, whatever you want, and just peg it with an exchange rate to a "real" currency (or not). Also, receipt scanning works and other Splitwise "premium" features are fully supported. It's free, open source, and as little telemetry as so on as possible.

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Actual performance

6points
3comments
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
46%46% 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: open source · Missing: https docs, excited, just released
35%35% 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 · Missing: plus, platform, intuitive
30%30% 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
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
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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