[unCited]
ProductCitation IndexAI InfluenceBlogBook
[unCited]/Tabnine
ProductCitation IndexAI InfluenceBlogBook
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AEO Score

34

Limited Presence

Avg Prompt Score

62

across 245 prompts

AI Share of Voice

62%

across 245 prompts

Category Visibility

#3

in AI Coding · of 30

Critical Issues

3

critical + high

Per-stage performance

🔍Discovery
165 category
Cited84%139/165
Share of voice64%avg
Engine consensus56%of engines
Competitors17.6avg/cited
Sentiment—no data
⚖️Evaluation
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
🛡️Trust
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
💰Conversion
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data

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

4
  • AI Coding3 of 30→
  • AI Code Assistantsnot yet measured→
  • AI Code Reviewnot yet measured→
  • AI-Assisted Developmentnot yet measured→

Executive 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

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