AI Visibility
measured18/100
Emerging · in AI Infrastructure
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals58/100
Some gaps
Avg Prompt Score
100
across 13 prompts
AI Share of Voice
100%
across 13 prompts
Critical Issues
3
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 Datasaur is visible in
1Executive summary
Datasaur is likely to be cited for evaluation-stage queries because it has strong G2 presence (29 reviews, 4.5★ per your pre-verified context) and first-party pricing plus an FAQ that answers NLP/LLM labeling questions. The biggest risk is conversion-stage and evaluation-stage “comparison” citation: while Datasaur has some first-party competitor framing (e.g., Datasaur vs. LabelBox), there is no clear evidence of first-party “[Brand] vs SuperAnnotate” and “[Brand] vs Labelbox” pages that are crawl-optimized for AI engines, so models may default to G2 Compare instead.
Based on audit of datasaur.ai · Oct 5, 2026