[unCited]
ProductCitation IndexAI InfluenceBlogBook
[unCited]/Comet.ml
ProductCitation IndexAI InfluenceBlogBook
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AEO Score

2

Limited Presence

Avg Prompt Score

5

across 453 prompts

AI Share of Voice

5%

across 453 prompts

Critical Issues

3

critical + high

Per-stage performance

🔍Discovery
317 category
Cited3%11/317
Share of voice3%avg
Engine consensus—
Competitors0.0avg/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 voice92%avg
Engine consensus92%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 Comet.ml is visible in

1
  • Data & Analyticsnot yet measured→

Executive summary

Comet.com is a B2B MLOps/LLMOps platform and already has strong AI-citation inputs from LinkedIn and Gartner Peer Insights presence, plus first-party comparison content (e.g., Comet vs Weights & Biases). The biggest AI citation risk is evaluation-stage “shortlist” queries that depend on crawlable structured data (SoftwareApplication/FAQPage) and robust review/analyst coverage—your TrustRadius footprint is extremely thin (1 review), and schema/LLM-crawlability signals weren’t confirmed in live checks. Highest-ROI fix: add/verify SoftwareApplication + FAQPage structured data on product/pricing/comparison pages and expand TrustRadius + comparison page coverage so AI engines can confidently cite Comet for “alternatives” and “vs” evaluation prompts.

Based on audit of comet.com · May 7, 2026

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