Blufa Is Free on the App Store on Christmas Eve

Hacker News

Hello HN, Sebastian Christiansen here, creator of Blufa. You might remember me introducing the open beta earlier this year. Well, I have some exciting news for this festive season! For today only, December 24th, Blufa is available for free on the App Store! This is a thank-you to the community and a chance for more people to experience the power of automatic face blurring in photos and videos. Blufa is the ultimate tool for sophisticated privacy protection, designed for everyone. It seamlessly processes any photo or video your iPhone can display, ensuring all visible faces are blurred with precision. Remember, this is a one-day-only offer, exclusively for December 24th! Don’t miss out on this opportunity to grab Blufa for free and join the forefront of photo and video privacy. As always, I welcome your feedback, questions, and suggestions. Let’s make digital privacy accessible to everyone! Happy Holidays, Sebastian Christiansen

Visit product View on Hacker NewsDec 24, 2023

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

91%91% 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 NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, open · Missing: mac, agents, macos

33%33% 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

16%16% 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.

Correct prediction on native model

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