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Teamates.io – Random video chats for professionals

Hacker News

Teamates.io – Random video chats for professionals

Hello HN, I built Teamates.io[0] - a place for professionals to have small coffee chats with a random partner right now. Think of it like a virtual coffeeshop where you can chat with strangers while you're taking a little break. It's in open beta and you can try using it right now. Please be nice and professional to each other :) I noticed over the course of pandemic I missed random coffee chats with my coworkers and random chats with strangers. I think it's important to have these unplanned conversations. I would really appreciate the feedback from you all, since I believe it's a pretty important problem to solve. Feel free to leave a HN comment or fill out a survey at the end of your call. Thanks, Aibek [0] https://www.teamates.io

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Actual performance

9points
6comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, 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
48%48% 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: video · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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