AI Visibility
measured81/100
Frequently Cited · in AI Coding
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals34/100
Weak fundamentals
Avg Prompt Score
67
across 263 prompts
AI Share of Voice
67%
across 263 prompts
Critical Issues
3
critical + high
How AI Visibility breaks down
in AI Coding
Composite = 60% coverage + 40% engine breadth, 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 Tabnine is visible in
5Executive summary
Tabnine is likely to be cited by AI engines for evaluation-stage queries (e.g., “Tabnine vs GitHub Copilot” and “best AI code assistant”) because it has a strong G2 presence and first-party comparison pages plus publicly accessible pricing. The single highest-ROI fix is to strengthen/verify structured data + crawlability for evaluation assets (SoftwareApplication/FAQPage/FAQ-style evaluation blocks) so AI engines can reliably extract “what it is / who it’s for / pricing / integrations” without relying on third parties.
Based on audit of tabnine.com · May 6, 2026