Invesaro

TrustMRR

Invesaro is a subscription-based web application that provides educational cryptocurrency market data and analysis tools. For a monthly fee, subscribers can browse market data for 500+ cryptocurrencies, view interactive price charts, track halving cycle timelines, and read weekly AI-generated market summaries. All content is strictly informational and educational, clearly marked with disclaimers. We do not facilitate, execute, or intermediate any cryptocurrency transactions.

Visit product View on TrustMRRMar 10, 2026Crypto & Web3 Software stripe

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Actual performance

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

48%48% 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

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

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

26%26% predicted probability of success on BetaList, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription, subscribers, active · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

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

Correct prediction on native model

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