Neucards – Privacy based digital contact card

Hacker News

Neucards is an end-to-end encrypted contact information sharing and updating iOS app that protects your identity while letting you keep in touch with people. I started working on neucards as a side project more than ten years ago, and I decided three years ago to go full-time and try to build a community around it. There are two major problems that neucards addresses. First, most people end up with contact lists that are hopelessly out of date. Over time, people move, change jobs, or add social profiles and unless they tell you, chances are you could lose touch. Second, your contact information ends up in the wrong hands. There has been a huge increase in robocalls, unsolicited emails, data breaches, and online scams that is driven by accessing a person's contact info. Even worse, with AI now being able to imitate a person's voice or other mannerisms, knowledge about the connections you have with others can be used against you. Neucards automatically updates your contact information for anyone who has your digital contact card. You control your contact information and who has access. This is possible because of end-to-end encryption. Neucards brings the same level of protection for your contact information as Signal or WhatsApp does for your chats. Privacy is built it. But, even with these protections, you can share your contact info with anyone. As an example, here is a link to my Social card: https://www.neucards.com/of/braddominy?id=M6TC5PLngD&k=4R98i... I'm excited about how much neucards has grown and what I have planned for the future to do even more to protect people's privacy. If you have any comments, please let me know. Brad https://www.neucards.com

Visit product View on Hacker NewsMay 16, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · 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: excited, ide, io · Missing: https docs, just released, exist

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

20%20% 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 · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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