I’

I’m an introvert, made an app to maintain relationships, added more AI

Hacker News

I’m an introvert, made an app to maintain relationships, added more AI

Hello again fellow hackers. I created this app and I expect it can help others like me, those with ADHD and those who simply want to be better at reaching out to friends and family and related. In the first post I made that got traction — https://news.ycombinator.com/item?id=27642977 — I received a lot of commentary. I hope there will be related commentary this time around, particularly with the new AI functionality, but, so long as the app is used with genuine intention, I truly feel the result is a net positive and this is consistently reflected in the feedback I receive from actual users of the app. So, why am I posting again? Because better AI is becoming more available/democratized and I’ve updated the app to support contextually-aware AI-based message generation. This has allowed staying in touch to become even more friction-free. I define the app as a smart communications assistant/tool for text messages, calls and email that helps making staying in touch as effortless as it can be. How is this app different from other personal CRM, automation and messaging tools? Well, the app is super simple to use and combines some functionality from all these areas. Unlike most personal CRM apps that are unable to make contact decisions based on recently received texts and calls, device automation apps that lack a CRM focus, and messaging tools that cannot provide AI-generated and contextually-aware messages for your current conversations, CommuniqAI intelligently integrates these three aspects. It cleverly keeps you connected with the people who matter most, with minimal interruption and distraction. In contrast to other related apps, manually logging or copying previous communications is unnecessary and notifications display your actual conversation histories, so you can quickly recall what you last touched upon. By default, the app will not take any action and largely act as a helpful reminder, and I recommend this type of use. When I originally submitted to HN the app was still in beta, but this is no longer the case. Also, there are no ads, logins or subscriptions. I’d love some more feedback; I feel the use of AI in “all the things” will become pervasive.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
93%93% 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: apps, user, new · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: users, communications, calls · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: adhd, ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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