We

We built an appliance with Raspberry Pi that backs up from the cloud

Hacker News

We built an appliance with Raspberry Pi that backs up from the cloud

http://picirus.com For Startup Weekend Tulsa, we created a small low-power appliance (built on Raspberry Pi) that you connect to your different cloud accounts -- Facebook, Flickr, Dropbox, etc. -- and it downloads a copy of all your stuff every night. I was thinking about all the people I love who share directly to the cloud, without a lot of planning for the case where their Facebook account gets hacked, their Dropbox account has a glitch, or one of these services they love goes out of business suddenly some day. We had a ton of fun building Picirus during Startup Weekend. I highly recommend -- if you haven't been to a SW in your area -- consider being a part next year... there is a definite quantifiable boost in your productivity to sit down with other engineers, focus your efforts, and get something built.

Visit product View on Hacker NewsNov 21, 2012

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

89%89% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide · 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.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

45%45% 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

40%40% 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

40%40% 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

20%20% 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.

Correct prediction on native model

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