Evaluate your website usability in seconds

Hacker News

Hello HN! I'm working on a project called desplega.ai, and today we wanted to share a free tool we built to find usability and accessibility issues in your sites. We used our engine for browser navigation (fully custom on top of Playwright) in conjunction with the axe-core engine ( https://github.com/dequelabs/axe-core ) to find the usability and accessibility issues as we explore your application in seconds. Feel free to try it out and let me know what you think! It's free and there's no sign-up required to see how it works and the live results (we may ask for your email if you want to see a cool report tho, I guess it's fair? :D) Note for vibecoders: You can just use your deployment URL and copy paste the full report to the v0/replit/lovable/bolt chat to fix them :D (shortcut https://app.desplega.ai/demo/landing-1?url=<your_url>) Cheers,

Visit product View on Hacker NewsSep 23, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: lovable, email, code · Missing: mac, agents, macos

77%77% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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