Video Messaging for Work

Hacker News

I built a tool that helps reduce meetings. Instead of long Slack threads or scheduled meetings, you send quick video messages to each other. - Slack is too noisy - Zoom is too heavy - Loom is too one-way Why is this different? We invented a "stream" which works like a real-time, multiplayer story. - It's low cognitive load and immersive - Catching up feels natural and effortless Yes, audio-only, text, and screen-clips are also supported. It's available on Mac + Windows. The free tier is perfect for standup at small startups (50 messages free every day). Warning: it's keyboard-driven. You must learn the keybindings.

Visit product View on Hacker NewsApr 25, 2026

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

89%89% 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: mac, slack · Missing: agents, macos, agent

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

53%53% 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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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