BoldContacts iOS app for elderly and people with disabilities

Hacker News

Hi HN, BoldContacts is an iOS app that shows your phone contacts one by one, using a big bold font, big bold buttons, and big bold photos. I am creating the app to help my folks, who are elderly, and who have terminal Alzheimer's Disease and Parkinson's Disease. The app goes on their iPhones and iPads, and accesses their existing contacts, and helps them call people. The app is significantly easier for them to use than the default iOS Contacts app, and than Siri voice control. Why would you try it? Because you want to help your folks, who are elderly, and they're having a harder time using the default Contacts app. With BoldContacts, you make it easy and friendly for them to see their friends and family, and easy for them to call and FaceTime. I welcome contructive feedback. The aim is to help people who are starting to experience vision issues, cognitive issues, motor issues, and the like. Success looks like these people connecting more with their friends, families, and caregivers. The app is free open source. To try it, search the Apple App Store for BoldContacts, or try the full source code in the git repo. You can email me at joel@joelparkerhenderson.com. https://github.com/sixarm/BoldContacts Ask me anything.

Visit product View on Hacker NewsNov 14, 2022

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2points

Did not reach leaderboard

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

89%89% 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: apple, email, using · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

70%70% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · 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.

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

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

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

16%16% 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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