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PrintNanny.ai, monitoring for 3D Printers

Hacker News

PrintNanny.ai, monitoring for 3D Printers

Hi! I'm the Founder of PrintNanny.ai - monitoring for desktop 3D printers. I just put together this online demo of PrintNanny's detection system. I'd love to hear what you think! The detection system usually runs offline on a Raspberry Pi 4. I didn't feel comfortable with other internet-connected solutions, so I built one that works without an internet connection. I ended up rolling a custom Linux distribution (PrintNanny OS) to package up the detection system and some of my favorite tools, like OctoPrint and Tailscale VPN. This is the first time I've made the detection available to play with, without having to install the whole PrintNanny operating system.

Visit product View on Hacker NewsMay 11, 2023

Actual performance

1points

Did not reach leaderboard

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77%77% 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 · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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