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Amf Floyd
Amf Floyd

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How We Built an Autonomous UX Auditing Agent

We recently shipped Parallax — an AI agent that automatically audits UX quality. Here's how it works and the challenges we solved.

The Problem

Traditional UX testing requires:

  • Hiring UX researchers ($80-150K/year)
  • Running quarterly research cycles (2-3 months)
  • Manual heuristic evaluation against Nielsen's 10 usability principles
  • Accessibility scanning (WCAG compliance)
  • Generating reports and prioritizing fixes

Result: Most companies do UX audits 2-4x/year. Problems discovered in Q2 don't get fixed until Q3.

The Solution: Autonomous Auditing

1. Crawling Smart User Paths

Instead of crawling every page, we identify critical flows:

  • Sign-up → Payment
  • Search → Product detail → Checkout
  • Login → Dashboard → Action

Each flow gets scored individually, so you see where users actually struggle.

2. Heuristic Evaluation

We implemented Nielsen's 10 Usability Heuristics as a scoring framework:

  • Visibility of system status
  • Match between system and real world
  • User control & freedom
  • Error prevention
  • Error recovery
  • Flexibility & efficiency
  • Aesthetics & minimalism
  • Recognition vs. recall
  • Documentation
  • Recovery from errors

Each is scored 0-100 based on page structure, copy clarity, interaction patterns.

3. Accessibility Scanning

WCAG 2.1 AA compliance checking:

  • Color contrast ratios
  • Heading hierarchy
  • Form labels & descriptions
  • Keyboard navigation
  • Focus indicators
  • Image alt text

4. Smart Prioritization

Not all issues are equal. We weight by:

  • Impact (how many users affected?)
  • Effort (how hard to fix?)
  • Criticality (does it block core flows?)

Why This Matters

  • Speed: Audit cycles go from weeks to minutes
  • Frequency: Catch regressions before they hit production
  • Scale: Run across 50+ competitor sites to benchmark
  • Cost: No hiring UX researchers for routine audits

Try It

parallax-ux.com – enter a URL, get a UX audit in 30 seconds.

Questions? Happy to discuss our heuristic scoring, how we handle dynamic content, or architectural challenges we solved.

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