Hi Tabi
Indie HackersTurn your trip into a personal offline app.
hi tabi didn't start as a product. It started as a tool we built for ourselves and our closest circle — we needed a reliable, fully offline way to follow a day-by-day plan abroad without burning through roaming data, and
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Did not reach leaderboard
Launch Intel predictions
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TrustMRRFits verified-revenue profile · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs70%70% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive48%48% 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, revenue19%19% 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, crypto1%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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