10 Dimensions of
AI Comprehension Intelligence
Every diagnostic dimension is engineered to surface a different layer of how AI systems perceive, categorize, and represent your brand.
AI Interpretation Diagnostics™
See yourself through AI eyes
The core intelligence layer. Analyzes how ChatGPT, Claude, Gemini, and Perplexity independently interpret your brand based on their training data and reasoning patterns.
Business outcome: Teams gain a clear picture of AI perception gaps before they become reputational liabilities in AI-mediated search.
Semantic Intelligence Map™
Map your brand's AI knowledge graph
Visualizes the conceptual relationships AI systems form around your brand — which categories, competitors, and concepts are associated with your identity.
Business outcome: Marketing and SEO teams can align content strategy with how AI actually categorizes their market.
Entity Relationship Graph™
Visualize brand entity connections
An interactive graph showing how your core business entities — products, services, markets, competitors — are connected in AI semantic space.
Business outcome: SEO and brand teams can identify which entity relationships to strengthen for better AI citation probability.
Interpretation Drift™
Measure AI description inconsistency
Quantifies how much AI systems contradict each other when describing your brand across different query contexts and reasoning paths.
Business outcome: Brands with high drift scores face significant risk of inconsistent AI representation — especially in voice search and LLM-powered recommendations.
AI Readability Score™
Your brand's AI comprehension benchmark
A composite 0–100 score calculated from 8 weighted diagnostic dimensions, providing a single benchmark for your brand's AI comprehension health.
Business outcome: A clear, executive-ready metric that quantifies AI comprehension performance and tracks improvement over time.
Citation Probability™
How likely is AI to cite your brand?
Measures the probability that AI systems will reference your brand as a recommended solution when answering relevant user queries.
Business outcome: Directly impacts AI-mediated lead generation and brand discoverability as LLMs replace traditional search engines.
Semantic Intent Analysis™
Are AI systems reading your intent correctly?
Analyzes whether AI systems correctly identify the business intent behind your products, services, and content.
Business outcome: Ensures AI systems send qualified traffic by correctly understanding what problems your brand solves.
Conversational Search Alignment™
Optimized for how people ask AI questions
Measures how well your brand's digital presence aligns with the natural language patterns used in AI-powered conversational search.
Business outcome: As search shifts to conversational AI interfaces, brands optimized for natural language queries gain significant discovery advantages.
Structured Intelligence™
Is your data machine-readable?
Evaluates how effectively your brand's structured data, schema markup, and knowledge graph signals are being utilized by AI systems.
Business outcome: Brands with well-structured data are significantly more likely to be cited accurately and confidently by AI systems.
Cross-Model Analysis™
Do all AI systems see you the same way?
Side-by-side comparison of how ChatGPT, Claude, Gemini, and Perplexity describe your brand — revealing where models agree, diverge, or misrepresent you.
Business outcome: Enables targeted optimization for specific AI platforms based on where interpretation gaps are most severe.