Remote notifications system in its early stages

Hacker News

So, I've created this notification system from scratch to send notifications from remote systems to local workstation/laptop/phone and it has came to that point it can be shown to people. Starting point for me was to send notifications from my IRC bouncer to my workstations and phone (which now works, yay!) but has extended to common purpose system. For example, if you are running long tasks on your server and want to get notify to you phone when its done, just do simple curl command after && ! Brief intro to get started and running server can be found here: http://lotsof.coffee/ All of this is open source and here comes the links: server - https://github.com/vhakulinen/push-server android app - https://github.com/vhakulinen/push-tool-android linux desktop client - https://github.com/vhakulinen/push-notify-daemon I've also been experimenting with the reddit's api to get notifications when there is new messages in inbox but that's not ready yet. Oh, and please don't crash the server if you find bugs, open up an issue on github :)

Visit product View on Hacker NewsApr 16, 2015

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4points

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

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69%69% 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 HuntOn track for Day 1 leaderboard · Strong signals: new, inbox, tasks · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

32%32% 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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