Is your organization invisible to the reasoning layer?
A high-level diagnostic audit to identify structural gaps in your AI visibility before the zero-click economy erases your market share.
No contracts. Clear verdict. Actionable next steps.
The Blind Spot in the Boardroom
Traditional digital metrics are hiding a critical reality: AI systems generate answers, not rankings. While your reports might show stable search rankings, the reasoning layers of ChatGPT, Claude, and Gemini may be entirely ignoring or misrepresenting your brand.
If your brand is missing or distorted in AI-generated narratives, the issue is not a lack of content, but a lack of structural clarity. Without a machine-readable "Truth Layer," your organization remains an ambiguous signal that AI models cannot confidently cite or recommend.
Measuring What Matters in the Agentic Web
Our Executive Audit provides a forensic snapshot of your brand’s AI health across three critical dimensions:
Entity Resolution Score
We measure whether LLMs identify your brand as a unique, verifiable entity or a generic industry term.
Citation Recall Rate
We calculate the frequency with which your primary sources are utilized as "Truth Anchors" for industry-specific queries.
Hallucination Risk Index
We identify specific areas where AI models are currently generating inaccurate or unverified claims about your products or services.
Extraction Efficiency
We test how easily "Compact Answer Units" can be retrieved from your current architecture compared to your top competitors.
3 Steps to AI Structural Clarity
Forensic Capture
Our tools perform a comprehensive sweep of your digital footprint to see your brand through the "eyes" of an AI bot.
Model Stress-Testing
We run standardized forensic prompts across major LLMs to establish your baseline "Entity Density".
The Executive Roadmap
You receive a prescriptive report that turns these signals into a technical fix-plan for your architecture.
You don’t buy visibility. You buy customers.
- AI Visibility Audit (where and how you appear today)
- Brand Mention Strategy (what AI should say about you)
- Citation Optimization (so AI repeats your name correctly)
- Competitive Visibility Map (who AI prefers today)
- Baseline Monitoring (so progress is measurable)
Daniel Ovidiu Banica
CEO @epoint and @marketos
the enterprise methodology
Powered by an enterprise-grade AI visibility framework
Brand visibility inside ChatGPT, Gemini, and Perplexity does not happen by chance. It requires a level of precision that goes far beyond traditional SEO or content marketing.
Behind this service sits AIVIS-OS (www.aivis-os.com), an advanced framework and operating system designed specifically for how large language models discover, interpret, and reuse information. While clients experience simple outcomes—being mentioned, trusted, and chosen—the underlying methodology is built on deep analysis of how AI systems crawl websites, identify brands, and decide what information is safe to cite. This includes modeling brands as structured entities, connecting them through verified relationships, reinforcing claims with evidence, and ensuring consistency across clusters of content.
You don’t need to understand entities, knowledge graphs, or AI indexing mechanics to benefit from them. What matters is that the methodology is rigorous, repeatable, and engineered for how AI systems actually work today. This depth is what separates temporary visibility from durable, compounding presence inside AI-generated answers.
AI Visibility Methodology
The offer
We’ve simplified the technical complexity into four actionable components for your business:
System Logic: Entity > Keyword
Most SEO is "spray and pray." We take a surgical approach, mapping your core services to unique Wikidata identifiers (QIDs). This eliminates disambiguation errors, ensuring that every AI model knows exactly who you are, what you do, and why you are the expert.
Outcome: Retrieval-First Design
We don't just "write content"; we build data pipelines. By serializing your knowledge into high-density JSON-LD, we decrease the computational effort required for AI bots to index you. When you make it easy for the machine to read, you make it easy for the machine to recommend.
Standard: The 10-Hour Workflow
Complexity is the enemy of execution. Our process follows a strict 10-hour implementation standard for every priority page, moving from entity inventory to forensic verification. You get a repeatable, scalable system that turns technical debt into a strategic visibility asset.
Talk to Our AI Visibility Expert
Effective AI visibility is more than just technology –
It's about understanding entities, knowledgeGraphs, Retrieval and Clusters.
Daniel Ovidiu Banica
CEO @epoint and @marketos
Any questions?
Quick answers to frequently asked questions about AI Brand Visibility
Here you find answers to the most common questions about our AI automation services. If you need more details, don't hesitate to contact us.
Haven't found your answer?
What is an AI Visibility Executive Audit?
Unlike a traditional SEO audit which counts backlinks and keywords, an AI Visibility Executive Audit is a forensic diagnostic of your brand’s standing in the “Reasoning Layer” of LLMs. It measures how systems like ChatGPT and Gemini perceive, verify, and cite your organization’s entities compared to your competitors.
What is the Hallucination Risk Index?
The Hallucination Risk Index is a proprietary metric that quantifies the probability of an AI model generating false information about your brand. High risk occurs when your entity signals are weak or contradictory, causing the model to “fill in the blanks” with statistically probable but factually incorrect data.
Why measure Extraction Efficiency?
Extraction Efficiency tests how easily an AI agent can retrieve a “Compact Answer Unit” from your site architecture. If your content is buried in complex DOM structures or narrative fluff, extraction efficiency is low, meaning the AI is likely to ignore your data in favor of a competitor’s machine-readable source.
