Built a Name Finder App for Islamic Names

Hacker News

Hi HN, I've recently noticed a lot of discussions about Islamic property names—how they carry cultural and spiritual significance and the challenges people face in understanding or choosing them. To address this, I built a Name Finder App as an effort to provide clarity and make the process more accessible. Features: 1. Find and explore property names with Islamic origins. 2. Understand their meanings and cultural context. 3. Easily browse through suggestions for inspiration. ### Tech Stack: * Backend: Python * Frontend: React * Database: PostgreSQL * Infrastructure: AWS I’d love to hear your feedback on this! Whether it’s feature suggestions, technical improvements, or anything else, your input would be invaluable. Here’s the link to check it out: https://www.jamaah.org Looking forward to your thoughts!

Visit product View on Hacker NewsNov 21, 2024

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

68%68% 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: lua, ide, io · Missing: https docs, excited, just released

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: context · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

25%25% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

13%13% 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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