GammaVibe Daily Ideas
Daily, AI-vetted startup ideas and architectural blueprints
I was curious if it was possible to automate ideation by building an agentic pipeline that extracts business signals from news and performs market research, so I build GammaVibe to prove this hypothesis.
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →58%58% 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.
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
30%30% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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