Open-source chat app that saves NO messages, anywhere, ever

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Inspired by Facebook's whistleblower confession about how Facebook (among some other apps) cares more about negative content and doesn't care about privacy, I decided to create an open-source chat app. This chat app doesn't save any history or messages in the database. Chat history is active as long as you are in the conversation screen, once you go back or close it, messages are not there. Some kind of "live chat". I made it open-source because I want people to be able to see how their data is being used and to see the truth behind the scene. By not open-sourcing the code it would by only my word "I'm not saving history", in this way it's tangible. I published the backend part on GitHub, the app is coming soon. You can follow me on Twitter (https://twitter.com/PozitivnaMirta) for more updates on my progress. Also you'll find there Github repos.

Visit product View on Hacker NewsJan 8, 2022

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

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: apps, code, open · Missing: mac, agents, macos

79%79% 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, io · Missing: https docs, excited, just released

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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