Exposure, a way to build photo narratives

Hacker News

I've been working with a colleague on a new product for amateur and pro photographers alike, called Exposure. It's launching into beta this Monday, and our goal is to create a place for composing and consuming thoughtful photo narratives that truly respects the content (i.e. no crufty UI). There's also a super smooth post creation experience we're pretty excited about. We'll be letting more folks in soon, so if you're a pro, semi-pro, amateur, or hobbyist photographer, it'd be great to get your feedback and/or interest. Here's an example profile: http://luke.exposure.so/ And an example post: http://luke.exposure.so/new-york Register for an invite if you're interested: http://exposure.so/invite Thanks!

Visit product View on Hacker NewsOct 12, 2013

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

79%79% 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: excited, io · Missing: https docs, just released, exist

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

18%18% 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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