Screen Canvas – Make Digital Signs Instantly Using Apple TV

Hacker News

Screen Canvas is the only app that lets you create stunning, customized digital signs directly on your Apple TV—instantly and effortlessly, using only your remote or even Siri! Perfect for everyone—from individuals crafting reminders or greetings, to businesses setting up real-time displays—Screen Canvas makes creating digital signage fast, taking just seconds right on your TV. Why it's different: No need for third-party apps, designing in a browser, or using complicated software filled with complex features. Screen Canvas is perfect for creating quick, simple signs that anyone can make—no tech skills required. Everything is done right on your Apple TV, with no setup hassles. You can save unlimited signs, add over 100 premium stock photos, customize colors, and enjoy an easy-to-use design library. The free version includes essential features, and a one-time Pro upgrade unlocks extras like more colors, extended character limits, a full image library, and no watermark. Designed for ease of use, Screen Canvas adds a polished, professional touch to any TV display.

Visit product View on Hacker NewsOct 30, 2024

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

95%95% 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: apple, apps, using · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% 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

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

Correct prediction on native model

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