creetr

TrustMRR

Creetr turns a product link into a ready-to-post AI UGC video ad in minutes. Paste a URL, pick an AI actor and hook, and get a 9:16 video with native audio, captions and auto-editing for TikTok, Reels and Shorts. Also includes competitor ad spy, a viral hook library and 50 free tools. A cheaper, faster alternative to Arcads and Creatify, or to hiring UGC creators.

Visit product View on TrustMRRJul 12, 2026Marketing Other B2C

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating1

MRR growth 30d-100.0%

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

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

48%48% 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: ide, io · Missing: https docs, excited, just released

44%44% 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

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

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

30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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TrustMRR2$256/moArtificial Intelligence