Event Alpha

TrustMRR

Event Alpha is a data-processing platform built for prediction market traders to extract an informational edge from earnings transcripts. It uses an outcome matrix to map management commentary to specific market results, replacing manual reading with data visualizations that highlight sentiment trends. The core feature is an AI-driven chat using RAG, allowing users to "talk to the data" to quickly uncover context and hidden details that others might miss.

Visit product View on TrustMRRFeb 25, 2026SaaS Software B2B

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Actual performance

Did not reach leaderboard

Launch Intel predictions

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TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, context, visual · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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