Beautiful, fast, web-based bill splitting

Hacker News

Hi HN: I really think I've perfected bill splitting - afaik this is the first app that let's you split items into fractions (e.g. splitting a pitcher into thirds). You just need to take a photo of the receipt and Torte will handle the math. This makes dining out way less stressful for you and your friends when someone shouldn't or can't split the bill evenly. Please enjoy and pressure test! (USD-only) I do recommend you download the app-based version for a smoother experience, but your friends do not need to download the app to join the bill and split. APPLE https://apps.apple.com/us/app/torte-fast-bill-splitting/id14... ANDROID https://play.google.com/store/apps/details?id=com.torte.pay (Torte was formerly a complete mobile order and mobile payment POS that I beta tested in several restaurants. I've walked it back to bill splitting in order to focus on other projects.)

Visit product View on Hacker NewsDec 2, 2022

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1points

Did not reach leaderboard

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

56%56% 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 HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

50%50% 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: io · Missing: https docs, excited, just released

47%47% 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: apps, google, way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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

20%20% 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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