compliance tracker

TrustMRR

Stop guessing which licences apply. Answer a few questions about country, legal form, and activity. Get a sourced checklist with official government links, due dates, and email reminders. AI explains

Stop guessing which licences apply. Answer a few questions about country, legal form, and activity. Get a sourced checklist with official government links, due dates, and email reminders. AI explains obligations in plain language — it does not invent new rules.

Visit product View on TrustMRRSep 7, 2026Software stripe nextjs

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

58%58% 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

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, activity · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, 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

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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