AI Visibility
measured25/100
Emerging · in Data & Analytics
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals46/100
Some gaps
Avg Prompt Score
100
across 30 prompts
AI Share of Voice
100%
across 30 prompts
Critical Issues
4
critical + high
How AI Visibility breaks down
in Data & Analytics
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.
Per-stage performance
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.
Executive summary
PostGIS is likely to be cited by AI engines for “how to use PostGIS” and “PostGIS vs [other spatial DB]” style technical questions because its documentation is crawlable and widely referenced (e.g., G2 has a PostGIS product page). The biggest AI-citation risk is evaluation/conversion-style queries (pricing, “is it worth it”, and structured comparison pages) where postgis.net lacks first-party, productized evaluation surfaces (pricing tiers, SoftwareApplication/FAQPage schema, and explicit comparison/alternatives pages).
Based on audit of postgis.net · Sep 1, 2026