A/B test images with your eyes using ARKit face tracking

Hacker News

Saccade uses ARKit face tracking to measure which image you actually look at longer in a side-by-side (well, top-and-bottom as it runs in portrait mode) comparison. Import a set of images, and it runs every possible pair, tracking your gaze for a dynamically-timed duration each (typically just a fraction of a second). It then ranks the images in descending order of how long your gaze lingered on each. You can then rerun the same batch of images to compound data over multiple tests, or start new. And of course you can easily share your results with friends and colleagues. Bonus: The Emoji Duel game is pretty fun for onboarding; our 4yo can't get enough of it. :) 100% free, no backend, no user auth, no data leaves your phone. Requires iPhone with Face ID.

Visit product View on Hacker NewsMar 24, 2026

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

80%80% 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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% 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, io · Missing: https docs, excited, just released

26%26% 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 · 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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