AI Visibility
measured51/100
Frequently Cited · in AI Infrastructure
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals61/100
Some gaps
Avg Prompt Score
42
across 656 prompts
AI Share of Voice
42%
across 656 prompts
Critical Issues
4
critical + high
How AI Visibility breaks down
in AI Infrastructure
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.
Categories PyTorch is visible in
1Executive summary
PyTorch.org is highly likely to be cited by AI engines for “what is PyTorch / how to use PyTorch” and “case study” style queries due to strong third-party review presence (e.g., TrustRadius) and extensive first-party documentation and case studies. The biggest citation risk is evaluation/conversion-style queries that expect SaaS-style comparison and pricing surfaces (e.g., “PyTorch pricing”, “PyTorch vs X” with purchasable framing); the highest-ROI fix is to add crawlable, evaluation-intent structured pages (FAQPage + comparison blocks) that explicitly answer pricing/selection questions in an AI-overview-friendly way.
Based on audit of pytorch.org · Sep 30, 2026