usecouncil.app

TrustMRR

The Council is a SaaS (Software as a Service) platform that provides a unified interface for interacting with multiple Large Language Models (LLMs) simultaneously. Customers pay a recurring monthly subscription to access premium features, advanced settings, and higher usage limits. The software is accessible immediately after payment.

Visit product View on TrustMRRDec 15, 2025Artificial Intelligence Software B2C

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating6

Launch Intel predictions

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

75%75% 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.

Hacker NewsStrong engagement from HN community · Missing: https docs, just released, open source

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, models · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: monthly · Missing: api, 000, profitable

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.

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

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

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

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

BetaListMay not resonate with beta-testers · Missing: web3, just like, small businesses

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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