AI UX intelligence system for product designers and founders
Free tree testing tool for testing information architecture
Stage
Startup
Established
Founded
2025
2021
Based in
IN
Not given
Pricing model
Freemium
Free
Pricing
Free: $0/month with 100,000 tokens (about 15 questions or 3 screen reviews). Pro Quarterly: $57 billed quarterly (about $19/month) with 1.9 million tokens (about 215 questions or 70 screen reviews). Pro Yearly: $131 billed yearly (about $10.92/month) with 1.9 million tokens.
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
Ask UX questions and get answers citing verified guidelines
Audit screens measuring contrast, tap targets and text sizes from pixels
Library of 50 free UX laws and guidelines
Multiple AI model comparison for design analysis
UX prompt optimization
Unified consensus on design decisions
Projects that remember product context
Every finding cites its source guideline
Access to Claude Opus 5, Gemini Pro and Deep Research on Pro plans
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
Every finding cites a verified guideline, not an opinion or guess
Measures what it claims using pixel-level data, not guesses
Built by certified UX professional with 19 years of practice
Answers backed by universal UX/UI/CRO principles and human psychology research
Instant feedback at every stage instead of waiting days for design reviews
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
ProUX