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I made the simplest budgeting tool to track expenses

Hacker News

I made the simplest budgeting tool to track expenses

Hello everyone, I’m excited (and a bit nervous) to introduce my first-ever SaaS product: Wingmann. I recently started earning some money as an intern 6 months ago, and it’s been a struggle to keep track of my income and expenses. I tried numerous apps, but they were either too complicated, had features I didn’t need, or had a paywall for essential features. Many had clunky UIs or too much friction to make quick entries. Late one night, while doom scrolling, I stumbled upon the 50/30/20 budgeting rule. It was a lightbulb moment for me. This simple split was exactly what I needed, but none of the apps I found natively supported this method. I tried to set it up in Notion but failed miserably after 4 hours. As a full-stack developer, I decided to build the tool I needed myself. I set a challenge to complete it in just 2 days because I couldn't afford to spend months on it and I had already wasted 6 months not tracking my expenses. Those were the most intense two days of my life, with no sleep and just coding. So, here it is: Wingmann. Features: Expense & Income Entry: Log your expenses and income in just a couple of clicks. Automatic Budgeting: Uses the 50/30/20 rule to automatically categorize your income into Essentials, Fun, and Future. Summaries & Insights: Get clear visual summaries of your spending habits to make informed financial decisions. I built Wingmann to be the simplest budgeting tool out there. No unnecessary features, no paywalls for the essentials, just straightforward budgeting and expense tracking. I’d love for you to try it out and let me know what you think. Your feedback would be incredibly valuable to me as an indie maker on this journey. Thank you!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
91%91% 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, visual, coding · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps, month · Missing: mobile apps, ios, personal
51%51% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, lua, ide · Missing: https docs, just released, exist
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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