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PillarLabAI – A reasoning engine for prediction markets

Hacker News

PillarLabAI – A reasoning engine for prediction markets

Hi HN, I’m the creator of PillarLab. I noticed that most people betting on prediction markets like Polymarket or Kalshi were either guessing or using generic LLMs that hallucinate data. I built PillarLab to solve the 'black box' problem of AI. It uses 1,720+ proprietary 'Pillars' (analytical frameworks) to guide the AI through rigorous logic, things like Sharp Money tracking, xG soccer models, and Line Movement. I’d love your feedback on the reasoning. Does the weighting of factors make sense to you? I'll be here to answer questions all day!

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, using · Missing: mac, agents, macos
68%68% 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 · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, 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
22%22% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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