Social media sucks, so I built a better rewarding one

Hacker News

Most social media platforms make creators chase likes, views, and algorithm gods—just to maybe earn something through ads or brand deals. I kept thinking: why is it still this hard to get paid for your work directly? So I built Premsi, a social app where creators can instantly market and monetize their digital content without sponsors, algorithms, or approval walls. You can sell locked messages (like photos, videos, or PDFs), create subscription groups, earn tips, or just get paid when someone likes your post in the premium feed. It’s already live on premsi.com and in the App Store. We’ve got over 2,000 users and creators have earned more than $10,000 so far—without needing a huge following. If you’re an artist, coach, photographer, model or just tired of juggling 5 platforms to earn from your content, Premsi gives you everything in one place. Still super early—but I think we’re onto something creators actually want. Would love your thoughts.

Visit product View on Hacker NewsApr 20, 2025

Share card

Actual performance

4points

5comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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.

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

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: reward, paid · 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

Similar products

Can we do social media differently and better?41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Can we do social media differently and better?

Hacker News3

Your Social Media Fingerprint (maybe NSFW)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Social Media Fingerprint (maybe NSFW)

Hacker News911

FAQ Off – Mitigate Mob Harassment on Social Media34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

FAQ Off – Mitigate Mob Harassment on Social Media

Hacker News1

Social Media Defaults for Mindfulness32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Defaults for Mindfulness

Hacker News1

Combat social media addiciton with foreign wikipedias38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Combat social media addiciton with foreign wikipedias

Hacker News1

Vers – Social Media as It Should Be32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vers – Social Media as It Should Be

Hacker News1

This is what social media could be41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

This is what social media could be

Hacker News123

Unbundling Microlearning from Social Media26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unbundling Microlearning from Social Media

Hacker News2

Publer34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Social Media Superhero

Indie Hackers33$400,000/mob2b

Mizo49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Handled

Product Hunt+1

Browse all products Analyze your launch