I made a "Chat with your budget" budgeting app

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I built JABA because I was frustrated with existing budgeting apps being overly complicated and rigid. While there are many budgeting apps out there (hence the name JABA "Just Another Budgeting App") this one is simpler and has a Chat with your budget feature. I also feel like there is a better way to do budgeting with the current state of AI. I want an AI assistant that helps me stay on track. I want it to text me, let me know every morning how I'm doing and how I should be spending or not spending. I haven't achieved that yet in this MVP but I hope to. Would love to get your feedback on this. Key features: - Chat with your budget - An AI assistant for your budget - Manual transaction entry by design - helps you stay mindful of your spending - Flexible budget periods (monthly, bi-monthly, or custom periods) - Completely customizable categories and budget structure - Smart debt payoff and savings projections - No bank connections required (v1) What makes JABA different: Philosophy: Most apps try to automate everything, but this often leads to miscategorized transactions and a disconnect from your finances. JABA embraces manual entry as a feature, not a bug. I'm also not married to this and may end up adding bank connections if I can figure out a good UX. Flexibility: Start budgeting from any date (even mid-month), create custom periods, and structure your budget your way. No forced categories or rigid systems. AI as a helper: The assistant is meant to be a friend to help you stay on track with your budget. Try it out on iOS: https://apps.apple.com/us/app/jaba-chat-with-your-budget/id6... Looking for feedback, particularly from others who: - Want to see what AI can do for budgeting and would like to help me achieve that - Need flexible budget periods - Want to chat with their budget

Visit product View on Hacker NewsNov 13, 2024

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

81%81% 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.

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

69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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.

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

20%20% 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: arr · Missing: mrr, revenue, profit

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, finances, smart · Missing: web3, crypto, cryptocurrency

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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