Tabstack Web Research

Tabstack Web Research

Product Hunt

Run a research agent with cited answers in a single API call

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Actual performance

168upvotes
27comments
Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, single · Missing: mac, agents, macos
90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal
66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
50%50% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% 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
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
13%13% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Correct prediction on native model

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