Delayed Send for Microsoft Teams

Hacker News

Hello HN, Pablo here from Appfluence. DelayedSend (https://delayedsend.com) is an add-in to schedule messages in Microsoft Teams. You can choose the time, the destination chat (personal or group), and of course the message itself. There is a dashboard to reschedule, edit, or cancel messages if you change your mind. We built this because we work with both Slack and Teams, and we noticed the big convenience gap between the two, with delayed/scheduled messages being one of the most glaring ones. On the technical side, the app was built in less than a month, on Azure App Service with NextJS, which was also a fun way to learn something new for some of us. The app is completely free, since it's a bit of a side project for now, but we expect to add some premium features in the future, such as recurrence, rich formats, delivery alerts, etc. I'd love your feedback! Happy to answer any questions.

Visit product View on Hacker NewsJun 27, 2022

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

87%87% 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: slack, new · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

59%59% predicted probability of success on TrustMRR, 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

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

30%30% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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