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Build your own Facebook, own your own data

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Build your own Facebook, own your own data

TL/DR: https://github.com/Qbix/Platform/blob/master/README.md We built it over the last 10 years and we’re giving it away. We are still working on updating the documentation to be as cool as for Angular and React. But it’s more than those frameworks. It includes a PHP backend with MySQL (pluggable) database support, with Node.js optional for web sockets realtime updates and offline notifications to apple/google/chrome/firefox/etc. On the front end it's got integrations with Cordova for releasing native apps in the stores, such as https://yang2020.app Just as an example if you wanted to build videoconferencing into your website, you would just do: Q.Streams.WebRTC.start(options) And if you want to have a secure user signup, forgot password, account management you just do: Q.Users.login(options) If you wanted to have events and schedule videoconferencing for various apps you build (eg group dating or collaboration) you would use Q.Calendars.addToCalendar() Reusable tools are placed like this: Q.activate( Q.Tool.setUpElement( element, “Streams/chat”, options ); ); or with jQuery: $(element).tool(name) .activate(options) You can have tools and subtools and pass options similar to React etc. Our goal is to build a growing ecosystem of well tested, reusable components that anyone can use, even if they are not very technical. Qbix separates concerns, e.g. text strings go into JSON files letting you translate your entire site with a script, then human translators can fix things. It's been audited by third party security firms, automatically generates SRIs, minifies your code, loads it on demand, and much more. Finally, it’s interoperable with everything else so you’re not locked in. Take a Wordpress site that uses React and drop a chatroom or videoconference in there and gradually start to build community features, an app in the store and reward people for inviting others etc.

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
90%90% 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, google, apps · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, video, google · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
44%44% 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: platform, users · Missing: plus, intuitive, reviews
39%39% 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
17%17% 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, reward · Missing: web3, crypto, cryptocurrency
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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