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Nauma new features (financial planning)

Hacker News

Nauma new features (financial planning)

Hi HN, We recently launched a few new features at Nauma, and I thought this community might be interested in learning about them. HELOC/SBLOC support. You can now model opening a line of credit and spreading withdrawals over time to keep your income below a desired threshold for tax and healthcare-cost purposes. This can be useful when you have a large expense, such as a home renovation, but want to keep your income below the standard deduction + 0% LTCG tax bracket, or when you want to diversify away from a concentrated stock position gradually. Demo: https://www.youtube.com/watch?v=b9rPxvBZFcc QCD support. You can now model charitable giving directly from a Traditional IRA. The model estimates actual QCD amounts each year based on the account owner's age, IRA balance, and IRS limits adjusted for inflation. Demo: https://www.youtube.com/watch?v=Qpldk1dArBI ACA and IRMAA constraints in the Roth Conversion Optimizer. Roth conversions can help reduce future tax spikes caused by RMDs, but they can also increase healthcare costs. With ACA and IRMAA constraints, we can help prevent situations where a family ends up overpaying for health insurance in retirement. Demo: https://www.youtube.com/watch?v=e2eHNIb3ynI I’ll be glad to answer any questions in the comments. I also have a few coupon codes for free lifetime access to Nauma for people who enjoy trying new tools early and giving feedback. DM me if you’re interested here: https://www.linkedin.com/in/alex-sukhanov/

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
54%54% 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: way · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: lifetime access · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, new, code · Missing: mac, agents, macos
25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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