Knightvision

TrustMRR

Important: A significant portion of recurring revenue is processed through Whop (separate billing platform) and is NOT reflected in the Stripe MRR or all-time totals shown above. Actual MRR is meaningfully higher. AI-powered ad intelligence and video generation platform. Users purchase credits to analyze social media advertisements and generate UGC-style video content using AI tools, with subscriptions billed via both Stripe and Whop.

Visit product View on TrustMRRMar 4, 2026Content Creation Apps B2C

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Actual performance

10customers

$378MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating1

MRR growth 30d+56.7%

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: user, stripe, using · 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.

TrustMRRFits verified-revenue profile · Strong signals: video, users, para · Missing: mobile apps, ios, personal

66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comFits revenue-generating acquisition profile · Strong signals: mrr, revenue, recurring · Missing: arr, profit, saas

58%58% 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, users · Missing: plus, intuitive, reviews

49%49% 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

24%24% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

24%24% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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