CAVIS
CAVIS
CAVIS (Conversational AI Visibility Intelligence System) is a framework for systematic simulation and analysis of AI visibility, developed by CitationLab AS. CAVIS structures AI search simulations around real user situations rather than simple keywords, and produces quantifiable visibility metrics across AI models.
CAVIS was developed by Krister Ross in response to the need for a structured method for measuring AI visibility. Traditional SEO tools measure ranking on keywords — but AI search is conversational, not keyword-based.
The CAVIS framework simulates entire user journeys: from information need to recommendation. It measures not only whether a brand is mentioned, but in what context — as a recommendation, as a source, as a comparison, or as a warning.
Frequently asked questions
What does CAVIS measure?
CAVIS measures brand visibility through conversational AI simulations: citation rate, sentiment, source status, and competitive positioning across AI models.
How do you use CAVIS?
The CAVIS methodology can be implemented with various AI visibility tools. You define the brand, industry, and target audience, and run relevant prompts systematically.
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KR
AI Search & Growth Strategist with 25+ years in digital marketing. Read more →