AI Visibility
measured87/100
Frequently Cited · in Vector Databases
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals25/100
Weak fundamentals
Avg Prompt Score
52
across 774 prompts
AI Share of Voice
52%
across 774 prompts
Critical Issues
6
critical + high
Shortlist Position
41/80
Challenger · Ai Infrastructure Discovery
How AI Visibility breaks down
in Vector Databases
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 Pinecone is visible in
2Your visibility gap
Pinecone surfaces in 41/80 Ai Infrastructure discovery prompts. Claim this profile to see which 39 prompts you're missing and how to win them.
Executive summary
Pinecone is already cited by AI for core “AI infrastructure” discovery prompts (e.g., training/deploying models and leading cloud infrastructure tools), and it has a meaningful G2 review footprint (39 reviews, 4.6 on G2). The biggest citation risk is evaluation-stage coverage for the specific buyer roles you listed (CRO/CFO/VP Eng/Systems Admin/etc.)—without role-and-JTBD-specific pages (and crawlable structured data), AI engines have fewer first-party surfaces to cite for those missing queries.
Based on audit of pinecone.io · May 6, 2026