The pitch deck we're raising $800k with

Hacker News

I believe strongly that information should be shared as freely as possible. This is one of the big reasons I started Localize, to make it an order of magnitude easier for information or knowledge to transfer from person to person, despite a difference in language. On openness, we've decided to share things companies normally don't share. We're starting with the pitch deck we're using to pitch investors for a $800k seed round we just started raising, plus snippets of our traction and growth charts. Why do this? The more we share, the more exposure other people have to our work. If our work is good, they can learn from us, if our work isn't good, we can learn from them! It's a win-win. So check out our video pitch, our deck, and let me know what you think.

Visit product View on Hacker NewsApr 30, 2015

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, 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, 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.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

24%24% 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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