We built Premagic – a tool that turns event attendees into marketers

Hacker News

At every event, tons of photos are taken, but they rarely get used well. As organizers, you post a handful on social media while the best moments are scattered across attendee phones. And if you’re hoping for engagement or visibility? It’s a grind. We built Premagic, an event tool that flips this problem. Here’s what we do: Instant Photo Sharing: We use AI to auto-select the best event photos and share them in real time with attendees. They get photos they love. You get organic visibility when they share (and they do). Branded Advocacy Posters: Personalized “I’m attending” or “I’m speaking” posters are generated automatically—no designer needed. Attendees become your event’s marketing army. AI Avatar Check-Ins: We turn event check-ins into an experience. Attendees can generate personalized, branded avatars on the spot—fun, shareable, and sponsor-friendly. We’ve tested this at over 2,000 events and seen a 3x increase in organic social reach for organizers. Event marketers and sponsors love it because it amplifies visibility without paid ads. We’re event tech folks trying to make photos and moments work harder—organically. Would love your feedback!

Visit product View on Hacker NewsDec 17, 2024

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Product HuntOn track for Day 1 leaderboard · 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.

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

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

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

34%34% 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 · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time, paid · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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