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Klever Desktop Beta: Next-Gen AI Usability Testing

Klever Desktop Beta: Next-Gen AI Usability Testing

Complete User Flow Testing Now Available

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Klever Desktop Beta: Next-Gen AI Usability Testing preview

About this plugin

About This Beta

Transform your usability testing with Klever's new desktop-powered solution. This beta version brings advanced automation capabilities to our AI-powered testing platform, enabling comprehensive prototype analysis and real browser interactions.


Demo


https://youtu.be/Dru78eszvsM


Key Features

* 🔄 Complete User Flow Testing

* 🤖 Advanced AI Analysis (GPT-4V)

* 🌐 Real Browser Automation

* 🎯 Natural Interaction Commands

* 📊 Comprehensive Testing Reports



Requirements

* KleverDesktop companion app (Download from GitHub)

* Chrome browser (auto-installed if needed)

* Choice of LLM:

* OpenAI API key

* Local LLM setup (e.g., Ollama)

* Enterprise configuration



Getting Started

1. Install KleverDesktop from GitHub

2. Launch the desktop companion

3. Install this Figma plugin

4. Connect your preferred LLM

5. Start testing your prototypes



Beta Status

* Optimized for macOS (Windows support in development)

* Desktop UI focuses on functionality (design updates coming)

* Regular updates and improvements planned


Help Us Improve

We value your feedback! Please share your experience and report any issues:

* 🐛 Report a bug

* 💡 Suggest a feature

* 📝 View existing issues



Looking for Single-Page Testing?

Try our classic Klever plugin for quick, individual page analysis.

Plugin Details

Version2
CreatedJanuary 30, 2025
Last UpdatedJanuary 30, 2025
CategoryPrototyping & animation plugins
CreatorJoo Hyung Park
Stats14 installs, 9 likes
PricingFree

Technical Details

  • API:1.0.0
  • UI:dist/ui.html
  • main:dist/code.js
  • Document Access:dynamic-page
  • Network Access:

    Required for WebSocket communication with KleverDesktop app and OpenAI API access

  • Editor Types:
    figma
  • Allowed Domains:
    • https://api.openai.com
    • https://figma.com
    • ws://localhost:8080