AI Visibility
measured26/100
Emerging · in Legal Tech
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals52/100
Some gaps
Avg Prompt Score
9
across 166 prompts
AI Share of Voice
4%
across 150 prompts
Critical Issues
5
critical + high
How AI Visibility breaks down
in Legal Tech
Composite = 50% coverage + 30% engine breadth + 20% position, measured in the brand's strongest category. Position and citation depth join the score once the aggregation pipeline captures them. This is the measured Visibility score — separate from AEO Readiness, which scores fundamentals.
Cited rate · share of voice · engine consensus · sentiment, broken out by buyer-journey stage. Sentiment is the net positive−negative skew across engines that cited the brand at this stage.
Lawcus is a B2B legal practice management SaaS and already has meaningful AI-citation inputs from G2 and Capterra (e.g., Capterra shows 4.8/5 from 63 reviews). The biggest risk for AI engines is evaluation-stage citation where they need crawlable first-party evidence (especially pricing + structured evaluation content); the single highest-ROI fix is to ensure Lawcus has crawlable, SSR pricing and evaluation pages that include SoftwareApplication/FAQPage-style structured data so models can cite Lawcus directly rather than only third-party review sites.
Based on audit of lawcus.com · Aug 29, 2026