UX Magic Inc.

TrustMRR

UXMagic.AI is a generative AI self-serve SaaS that enables prompts, screenshots, URLs to editable Figma, Webflow, framer files with simple copy paste.Further UXMagic enables sectional editing and changes with just prompting. Our MCP connects with all IDEs including Claude, Cursor and others. We also have a go live feature to take your website live in seconds. We have over 100,000 Signups in the last one year and 25000+ Traffic on our site monthly.

Visit product View on TrustMRRFeb 20, 2024Design Tools Software Both

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Actual performance

166customers

$5,250MRR/mo

Made the leaderboard

Traction signals

Domain Rating42

MRR growth 30d-11.5%

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, claude, mcp · Missing: mac, agents, macos

93%93% 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 · Strong signals: including · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% 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, 000, io · Missing: https docs, excited, just released

47%47% 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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

26%26% 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

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

Correct prediction on native model

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