VentureLens
Indie HackersAI that analyses startup pitch decks like a VC in 60 seconds
The idea came from helping a family friend evaluate a startup investment. We used AI to analyse the pitch deck and quickly surfaced strengths, risks, and missing information. It saved a lot of time and sparked a thought
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos81%81% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal29%29% 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, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive15%15% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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