Vetorizador

TrustMRR

Vetorizador is an innovative web platform that simplifies image processing for designers, entrepreneurs, and content creators. Using advanced technology, Vetorizador offers tools for automatic image vectorization, intelligent background removal, and resolution upscaling, ensuring professional quality for print and digital use. The platform operates on a freemium model, with Premium plans and individual credits, and includes PRO tools for CNC/Laser/Plotter.

Visit product View on TrustMRROct 1, 2025Utilities Consulting B2B

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Actual performance

2customers

$17MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating18

MRR growth 30d-4.1%

Launch Intel predictions

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

76%76% 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.

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

74%74% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: entrepreneurs · Missing: mobile apps, ios, personal

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% 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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

9%9% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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Product Hunt+8

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