Motion-first React components for shadcn and AI agents, with every curve already tuned
Free tree testing tool for testing information architecture
Stage
Not given
Established
Founded
Not given
2021
Based in
GB
Not given
Pricing model
Freemium
Free
Pricing
Free: 65 open source components under MIT license. Pro Solo early-bird: $149 (regular $199). Pro Team early-bird: $349 (regular $449). One payment covers all current and future Pro components.
Free for unlimited tree testing and card sorting studies, unlimited participants and responses, and full analysis. Participant recruitment through UXbeam's panel starts at $1 per participant-minute.
Key features
65 free components under MIT license
31 Pro components with source code included
MCP server for AI agent integration
Works with Next.js 16 and React 19
Light and dark mode support
Respects reduced-motion settings
Tuned motion springs and curves
Concentric corner radius design
Markdown documentation for AI models
New Pro components added weekly
Unlimited tree-testing studies and participants
Leading-task detection to catch biased wording
Path replay visualization of participant navigation
Task outcome breakdown into direct, indirect, and elsewhere
Full-scenario completion tracking across multiple tasks
Mobile-compatible participant experience
Integrated card sorting with tree testing workflow
Multiple valid destinations per task
Iterative testing with versioned results
Complete CSV export of participant-level results
What makes it different
All components tuned with motion springs and curves optimized per interaction
Built-in MCP server enables AI agents to automatically install components
One-time lifetime payment covers all current and future Pro components
Source code ownership with MIT and commercial licenses
Concentric corner radii maintained across all components
No credit card required and truly unlimited at no cost
Built-in methodological safeguards prevent common research mistakes
One-screen setup lets researchers create tests in minutes
Mental Model Detection identifies competing ways different user groups organize content
AI-assisted participant recruitment with audience targeting
Eased