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CharitySense a donor-centric data browser

Hacker News

CharitySense a donor-centric data browser

I'd like to share with you a project I've been working on called CharitySense. It's a straightforward and user-friendly website designed to help donors like you make more informed decisions when it comes to giving. On CharitySense, you can view human development indicators from countries worldwide, such as poverty rates, literacy rates, and access to clean water. I've also gone through all approximately 3.9 million non-profit tax forms, covering 500,000+ non-profits. The data browser allows you to quickly get an idea of the financial health and impact of the organizations you're interested in supporting. The idea is to give donors the ability to find the greatest need and then quickly find a relevant charity. It would be great to get your feedback and hear about any frustrations you have with the current giving process. Take a look and let me know your thoughts!

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84%84% 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: user · Missing: mac, agents, macos
84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: friendly · Missing: plus, platform, intuitive
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue
10%10% 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.

Incorrect prediction on native model

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