Part of GEO Suite
AI Visibility
Consolidated AI presence panel
What are LLMs and why do they matter for your business?
LLM stands for Large Language Model. These are the artificial intelligence systems behind tools like ChatGPT, Google Gemini, Claude, and Perplexity. They work by processing enormous amounts of text to learn human language patterns, which enables them to answer questions, generate content, and hold natural conversations.
When a user asks ChatGPT "what's the best project management tool?" or asks Perplexity "which laptop should I buy for graphic design?", the LLM analyzes everything it learned from the web and selects the sources it considers most trustworthy to build its response. If your brand, product, or website doesn't have the right signals, the model simply won't include you in that answer, and your competition will take that spot.
Google AI Overviews is Google's version of this technology: instead of showing just a list of links, it now generates a direct AI-powered answer at the top of search results. This means the first result many users see is no longer a link to your site, but an AI-generated response that may or may not mention you.
In short: LLMs are the new intermediaries between your business and your potential customers. More and more people use these tools to research, compare, and decide what to buy. AuraMetrics helps you ensure that when AI answers questions about your industry, your brand is part of the answer.
What it does
AI Visibility is the consolidated panel showing how your brand appears across AI engines (ChatGPT, Gemini, Perplexity, Google AI Overviews). It combines data from multiple AuraMetrics modules into a unified view organized across 5 pillars: Entity Authority, Structured Data, Trust Signals, Content & Citation, and an overall Health Score. Unlike individual modules that audit a specific aspect, AI Visibility gives you the complete picture of your AI presence in one place. It's the starting point for understanding where you stand and which areas need attention. The panel updates automatically every time you run an AuraMetrics module. No additional configuration needed: simply run analyses and AI Visibility reflects results in real time.
Why it matters
Without a consolidated view, it's impossible to prioritize. You might have excellent Schema.org but weak trust signals, or deep content but poorly defined entities. AI Visibility shows you where the critical gaps are. LLMs evaluate multiple signals simultaneously when deciding what to cite. A brand with good content but no structured data loses to one with both. The Health Score tells you how you're doing overall. AI Visibility also lets you track progress over time. After implementing improvements, you can see how they impact your overall AI visibility.
How it works
AI Visibility automatically aggregates data from your Content Readiness, AI Understanding, Trust Auditor, Schema Validator, AI Visibility Gaps and Answer Monitor analyses. It uses a machine learning algorithm that weights individual scores based on each pillar's relative importance for your industry. The Health Score is not a simple average: the model assigns dynamic weights based on industry benchmarks. For example, for eCommerce structured data (Product schema) weighs more than for a content blog, where content depth has greater impact. Each pillar breaks down into sub-metrics you can explore to understand exactly what's impacting your visibility.
Metrics you get
Recommended use cases
Frequently asked questions
What is the Health Score?
A 0-100 score summarizing your overall AI visibility. It's calculated using a machine learning model that weights each pillar's scores (Entity Authority, Structured Data, Trust Signals, Content & Citation) based on relative importance for your industry. It's not a simple average: weights are dynamically adjusted.
What does Entity Authority measure?
Evaluates how well LLMs can identify and contextualize your brand as an entity. Includes brand name clarity, consistency across digital properties, Knowledge Graph connection, category co-occurrence, and semantic isolation.
What are Trust Signals?
The trust indicators LLMs use to decide if your content is a reliable source: visible author, publication dates, HTTPS, About page, media mentions, authority backlinks, NAP consistency, and verifiable E-E-A-T signals.
Do I need to run all modules for it to work?
No. AI Visibility shows data from whichever modules you've run. The more modules you complete, the more accurate the Health Score. With 2-3 modules you get a useful view; with 5+ you get a complete picture.
Does the panel use machine learning?
Yes. The Health Score weighting algorithm uses a machine learning model trained on industry data to assign dynamic weights to each pillar. This means the metrics most important for your industry weigh more in the final score.
How often does it update?
It updates automatically every time you run an AuraMetrics module. No additional action needed: the panel reflects the most recent results in real time.
How is it different from individual modules?
Individual modules (Content Readiness, AI Understanding, etc.) perform deep audits of a specific aspect. AI Visibility aggregates all those results into a consolidated view so you can see the big picture and prioritize.
Can I see progress over time?
Yes. The panel includes a GEO Score trend for the last 30 days, showing whether your visibility is going up, down, or stable. This lets you measure the impact of improvements you implement.