SettleFast – the easiest way to split group expenses, no headaches

Hacker News

Hey HN, I built SettleFast ( https://settlefast.io ) after getting frustrated with how existing expense-splitting apps work. Most impose arbitrary limits or push you into recurring subscriptions just to manage group payments. I wanted something more straightforward. SettleFast is a lightweight web app that makes it easy to track shared expenses and simplify debt calculations. No forced app downloads, no complex onboarding—just create a group, add expenses, and let the algorithm optimize repayments. If you need more flexibility, there’s a one-time upgrade instead of a monthly subscription. Would love to hear your thoughts—especially if you’ve built or used similar tools before!

Visit product View on Hacker NewsMar 23, 2025

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

72%72% 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: apps · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, month, monthly · Missing: mobile apps, ios, personal

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

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

48%48% 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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: recurring, subscription · Missing: arr, mrr, revenue

25%25% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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