HUD-like live annotation and sketching app for macOS

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Hey all! I'm happy to announce we've finally released our 2nd macOS app, Draw Over It, a tiny desktop app that enables drawing, highlighting, or annotating directly on top of anything on your Mac. I've always wanted something like this for instant and unobtrusive sketching and annotation for pair programming and demos. I always found the standard web-based diagram and drawing tools a bit too cumbersome. So we built a simple overlay that could appear over any window or app with one shortcut. It doesn't collect any user data and doesn't require any system permissions - it's sandboxed. It all stays on your device. You can export your annotations to a PNG with one click - or just take a screenshot if you need the background too. It offers a slim but functional toolkit for every day tasks: - Global hotkeys, hit a shortcut and start drawing over any app - Multiple tools, pens, shapes, highlighters - Per-screen canvases, each monitor gets its own space - Focus mode, temporarily blur the background to emphasize what matters - Low footprint, no subscriptions, no sign-ups, no data collected - Localization, the app is translated to 14 languages These two reasons make it different from other canvas apps, it's simple, lean and keeps your data on-device only. It’s a one-time purchase ($2.99) on the Mac App Store. I’d love feedback and suggestions for improvements!

Visit product View on Hacker NewsOct 29, 2025

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

98%98% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

43%43% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% 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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