LLM Perception
See how AI assistants describe the brand across visibility, accuracy, sentiment, recommendation, and citation context.
- AI answer visibility
- Factual accuracy
- Sentiment and recommendation signals
- Prompt-level evidence trails
VectorGap turns LLM Perception, Web Perception, and GEO Performance into one audit loop: understand the answer gap, trace the evidence, fix the public truth layer, and re-run with client-ready proof.
Brand Perception Index
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Three-part audit loop
The public promise is simple: show agencies where AI answers come from, what the open web reinforces, and whether the client site is extractable enough to become a reliable source.
See how AI assistants describe the brand across visibility, accuracy, sentiment, recommendation, and citation context.
Understand how review sites, search results, social/forums, news, and blogs frame the brand before AI systems compress that evidence.
Audit whether pages are structured so AI systems can extract, trust, and cite the right entity facts.
Run audit
Read the signal map
Open the exact prompts and evidence
Ship fixes
Re-run and prove movement
Product preview
The protected app uses quiet hierarchy: hero actions, BPI detail, trend-first context, collapsible audit history, prompt links, and GEO radar/score history only where they help operators act.
Every premium audit pattern is designed to be forwarded, debugged, and repeated: short audit IDs, direct prompt/evidence links, trend context, and client-ready reporting without unsupported performance claims.