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Selenar

On-device AI that catches distractions on your Mac

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Selenar notices content you choose to avoid in your active Mac window: porn, feeds, shopping and news. Choose Leave it, 10 more minutes or Wrong call. Recognition is fully on-device, without screenshot, window text or page address uploads or external AI APIs.

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PH · launched Oct 16, 2026 · 1 upvote (top 67%)

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Could you build this?

Partial The app shell and window tracking are doable, but accurately classifying screen content (porn, feeds, shopping, news) on-device without screenshots needs a trained classifier that vibe coding can't produce on its own.

What it would actually take: Use macOS Accessibility and window-metadata APIs to detect the active app and window, then run a small on-device classifier, likely a fine-tuned vision or text model, in Core ML. The hard part is building a labeled, diverse training dataset and tuning it for low false positives without storing screenshots. Expertise needed: ML engineering for on-device models and data curation.

Competitors

Other products that read as similar to this one : 99 launches clear the similarity bar, closest 8 shown.

Attention rank: #54 of 100 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 281 days after the earliest competitor.

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