Our little bootstrapped startup is powering CNN's ticker for NYE

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Our little startup you've never heard of, called Vidpresso, is powering CNN's New Year's Eve social media ticker! It's a huge accomplishment for us. We're originally Utah based (our other employees are in NM and Karachi though) https://pbs.twimg.com/media/Bc3GdRrCUAAqLaN.jpg:large I'm posting this more out of sheer excitement than anything. I wanted to share that any startup anywhere can have exciting wins like this... regardless of whether you're in SV, went to MIT, or whatever. Just make something people want, and it'll work out. In 2014, start the thing you've been putting off. Maybe you'll have a fun new years like us next year! :) As a company, our goal is pretty ambitious: We want to change the way video is produced, so we're starting with the big guys and working our way down to the little guys. We're not hiring (yet) but if things like this appeal to you, we should definitely be friends. We have a writeup of our dreams here: http://www.vidpresso.com/blog/secret-vidpresso-master-plan

Visit product View on Hacker NewsJan 1, 2014

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

86%86% 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: new · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: video, way · Missing: mobile apps, ios, personal

59%59% 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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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.

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