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

78

Strong Presence

Avg Prompt Score

72

across 828 prompts

AI Share of Voice

72%

across 828 prompts

Critical Issues

5

critical + high

Shortlist Position

62/80

Leader · Agent Frameworks Discovery

Per-stage performance

🔍Discovery
525 category
Cited82%433/525
Share of voice71%avg
Engine consensus48%of engines
Competitors10.3avg/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 LlamaIndex is visible in

2
  • Agent Frameworks4 of 21→
  • AI Agents11 of 128→

Your visibility gap

LlamaIndex surfaces in 62/80 Agent Frameworks discovery prompts. Claim this profile to see which 18 prompts you're missing and how to win them.

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Executive summary

LlamaIndex is already cited for agent-framework discovery queries (e.g., customer support/customer success/QA automation/integration), but it is weak for evaluation-stage and conversion-stage citation because first-party evaluation assets (pricing + structured comparison/evaluation pages) are not clearly crawlable. The single highest-ROI fix is to publish/SSR an evaluation hub that directly answers the missing buyer questions (service delivery, microservices, IT support, workflow optimization) with FAQPage + SoftwareApplication-style structure so AI engines can cite it for those exact prompts.

Based on audit of llamaindex.ai · Jun 8, 2026

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