AI-Powered Browser Tab Manager – TabMate

Hacker News

Hello HN, My friend and I have spent the last month building an AI-powered browser tab manager. It's a Chrome extension that automatically categorizes all tabs into topics. It also supports some basic organization features like custom groups and locked groups (groups that AI doesn't touch). We would like to experiment with a few other things like nested folders, sync with browser tab grouping, user controlled prompt & categories soon! At the moment we just started looking for early adopters to help us test it + provide suggestions and feedback! Please consider giving it a try if this sounds interesting to you! (Or tell us here why it's a terrible idea and how it could be more useful! ;D) Thank you! -Lance

Visit product View on Hacker NewsJan 19, 2024

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Actual performance

6points

3comments

Did not reach leaderboard

Launch Intel predictions

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

83%83% 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 · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created

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

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% 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

39%39% 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

12%12% 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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