FlowLeap

TrustMRR

FlowLeap is a desktop workspace (a VS Code fork) with a patent-trained agent that searches EPO, USPTO, WIPO, PATSTAT, and the literature live, then drafts, analyzes, and reports with every finding cit

FlowLeap is a desktop workspace (a VS Code fork) with a patent-trained agent that searches EPO, USPTO, WIPO, PATSTAT, and the literature live, then drafts, analyzes, and reports with every finding cited. It covers the full patent lifecycle — invention disclosure, prior-art search, claim drafting, office-action response, FTO, invalidity, infringement charting, landscape and portfolio analytics.

Visit product View on TrustMRRJun 1, 2026Artificial Intelligence Software stripe

Actual performance

1customers

$16MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating2

Launch Intel predictions

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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto

59%59% predicted probability of success on BetaList, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: agent, code · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, 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: io · Missing: https docs, excited, just released

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

28%28% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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