System StatusOnline
NAV
Audit report: how ChatGPT, Gemini, Claude, and Perplexity perceive and recommend your brand. What LLMs know about your business and how to change the narrative.
I conduct a systematic audit of your brand's visibility across major AI models (ChatGPT-4, Gemini 1.5, Claude 3.5, Perplexity). I test 100+ industry queries, document how LLMs describe your company, products, and services, benchmark against your competitors, and deliver a prioritized action plan for improving your position in AI-generated responses.
Report from 100+ query tests in ChatGPT, Gemini, Claude, and Perplexity — a complete map of how AI perceives your brand today.
Comparative analysis against Top 5 competitors — who is cited more frequently than you, what content and signals they use to achieve that position.
Identification of incorrect or outdated information about your company in LLM responses, with a recommendation on how to correct it.
GEO gap map: industry topics where your brand should be the cited authority but isn't — a ready list of content opportunities.
Prioritized action plan with difficulty estimates and potential impact on AI visibility for each recommended action.
I create a set of 100+ queries covering brand queries (company name), category queries (industry, services), informational queries, and comparison queries — tailored to your market.
I systematically test all queries in ChatGPT-4, Gemini 1.5, Claude 3.5 Sonnet, and Perplexity, document each response, and record your brand's mention frequency.
I analyze results vs. competitors, identify patterns in content and signals that cause more frequent citation, and document factual errors in brand descriptions.
I deliver a detailed PDF report with findings, root cause analysis, and a prioritized action list with ROI estimates for each GEO recommendation.
It depends on the model. Perplexity and SearchGPT have access to a live web index. GPT-4 and Claude have a training cutoff date (typically 6–12 months in the past). The audit shows what each model knows separately.
Direct correction of LLM data is impossible — but it can be fixed through external sources. Updating Wikidata entries, Wikipedia (if you qualify), industry media, and your own content influences future training cycles and RAG.
I recommend quarterly — models update, new versions have different knowledge and behaviors. For companies actively building GEO, monthly monitoring is standard practice.
More modules inside "AI-GEO" — together they form a complete system.
Building your brand entity in Google Knowledge Graph via Schema.org and sameAs. AI models like ChatGPT and Gemini will start recognizing you as an industry authority.
View moduleGEO (Generative Engine Optimization) — content optimization for citations by ChatGPT, Gemini, Claude, and Perplexity. Your brand as the source of truth in AI-generated answers.
View moduleContent optimization for Siri, Google Assistant, and Alexa voice queries. Your site as the Featured Snippet (Position Zero) for voice questions in your industry.
View moduleContent and site architecture optimization for next-gen AI search engines — Perplexity, SearchGPT, and Gemini Search. Be the cited source, not just a link in the results.
View moduleInitiate protocol. Establish connection. Let's build something loud.