RESTfender – Connect and secure your IoT devices

Hacker News

Hi HN, I'm Jay and my cofounder and I have been working on RESTfender to help connect and secure IoT devices. Would love to hear feedback. While there are some IoT platforms out there, we're focusing primarily on the problem of botnets and managing devices. We use machine learning to track and automatically categorize bots. The app: https://app.restfender.com Website: https://restfender.com IoT Camera example: https://iot-cam.restfender.com (the goal is to find a place to attract more attention like a bird nest, hamster on a wheel, hummingbird feeder, etc.)

Visit product View on Hacker NewsAug 26, 2017

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5points

2comments

Did not reach leaderboard

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

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% 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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, using · Missing: agents, macos, agent

31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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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