Find out exactly where your brand is invisible to AI search - and what to do about it. We audit your presence across ChatGPT, Perplexity, Google AI Mode, Claude, and Gemini.
Request My Free AuditAI SEO is the practice of optimizing your website and content so your brand is visible across both traditional search engines and AI-powered answer platforms - including Google AI Overviews, ChatGPT, Perplexity, Claude, and Gemini.
In 2026, a growing share of B2B buyer research happens inside AI systems, not on page one of Google. A buyer looking for a cybersecurity vendor does not search Google and click ten links. They open ChatGPT or Perplexity, describe their problem, and act on whatever the AI recommends. If your brand is not in those recommendations, you do not exist in that buyer's evaluation.
AI SEO brings together three distinct disciplines:
Optimizing for traditional Google and Bing rankings through technical health, content quality, and authority signals.
Structuring content so AI answer engines and Google AI Overviews extract and surface it as a direct response to user queries.
Building the brand authority and content depth that causes large language models to cite your brand in generated responses.
An AI SEO audit tells you exactly where you stand across all three - and what to fix first.
Most SEO audits stop at technical issues and keyword gaps. An AI SEO audit goes five layers deeper - covering every signal that determines whether AI systems find, understand, trust, and cite your content.
AI crawlers behave differently from Googlebot. They struggle with heavy client-side rendering, JavaScript-dependent content, and pages that load too slowly. Your audit checks server-side rendering status, page speed scores, robots.txt rules, sitemap completeness, llms.txt presence, and whether your most important content is accessible to AI crawlers at all.
AI systems understand the web through entities - named people, companies, products, and concepts - not just keywords. Your audit maps how well your brand is established as a recognized entity, checks structured data, identifies missing schema types, and validates existing schema for errors.
Answer engines extract content that is clearly structured, directly answers questions, and uses natural language that matches how people ask queries. Your audit reviews heading hierarchy, definition blocks, question-format headings, answer-first paragraphs, internal linking depth, and reading level.
We test 50+ buyer-intent prompts across ChatGPT, Perplexity, Google AI Mode, Claude, and Gemini - the exact queries your target buyers are typing - and map which brands get cited, which get ignored, and where the gaps are.
Your audit evaluates named author attribution, author credential schema, external citation quality, domain authority, backlink relevance, topical depth, and whether your brand is mentioned on credible third-party sources that AI systems trust.
The terminology around AI search optimization is fragmented - different platforms and agencies use different acronyms for overlapping concepts. Here are the definitive definitions for the terms that matter.
The practice of structuring content so it gets selected as a direct answer by AI-powered search tools, Google AI Overviews, Bing Copilot, and voice assistants. AEO techniques include question-format headings, concise answer blocks, FAQPage schema, and structured data markup that makes content easy for AI to extract.
The practice of building content authority and brand depth so that large language models - ChatGPT, Perplexity, Claude, Gemini - cite your brand in their AI-generated responses. GEO focuses on original research, factual density, authoritative sourcing, and entity recognition.
AI Overviews is Google's feature that generates a synthesized answer at the top of search results, above the organic blue links. Optimizing for AI Overviews means structuring content so Google's systems select it as a source for the generated answer.
A broader term for any strategy aimed at improving how large language models perceive, understand, and reference your brand. LLMO encompasses both AEO and GEO tactics, plus entity optimization, training data visibility, and brand mention strategy.
The practice of establishing your brand, products, people, and content as recognized named entities in the knowledge graphs that Google and AI systems use to understand the world.
Experience, Expertise, Authoritativeness, and Trustworthiness - Google's quality rater framework for evaluating content. AI systems use similar signals to determine which sources to cite.
An emerging web standard - a plain-text file at yoursite.com/llms.txt - that tells AI crawlers and large language models what your site covers, which pages are most important, and how your content should be interpreted.
A brand's measurable presence across AI search platforms - the frequency and prominence with which a brand is cited, recommended, or referenced in AI-generated responses across ChatGPT, Perplexity, Google AI Mode, Claude, and Gemini.
Each major AI platform sources, weights, and presents information differently. Optimizing for one does not guarantee visibility on another. Here is what you need to know about each platform.
ChatGPT's knowledge comes from training data plus real-time web browsing. For brand citation, the highest-leverage actions are publishing on indexed sites, building strong external mentions, and using definite, factual language rather than hedged claims.
Perplexity performs live web searches and cites sources directly. Ranking in Perplexity requires strong SEO fundamentals, fast server-side rendered pages, clear answer-first structure, and frequent publication.
Google's AI surfaces synthesize answers from pages it already indexes and trusts. To be featured, your page needs strong rankings, clear question-matched headings, schema markup, and topical authority across related content.
Claude visibility depends on authoritative external sources, original research that other sites cite, and content clearly attributed to named human experts with verifiable credentials.
Gemini combines Google's search index with language model training. Optimization is closely aligned with Google SEO best practices, with added emphasis on entity optimization through Google's Knowledge Graph.
Microsoft Copilot blends Bing Search with OpenAI models to generate answers grounded in live web results. Visibility improves through strong Bing SEO, structured data, authoritative backlinks, fast-loading pages.
Most AI SEO guidance is written for e-commerce, consumer apps, or media publications. B2B technology companies face a different set of challenges - and a different set of opportunities.
Lower search volume, higher buyer intent. B2B buyers search less frequently but with far more intent. A query like "best identity verification API for enterprise" has a fraction of the volume of "best running shoes" - but the person asking it is evaluating a six-figure purchase.
Longer evaluation cycles. B2B buyers research over weeks or months, asking AI assistants multiple questions at different stages of the funnel. An AI SEO audit maps your presence across early-stage, mid-funnel, and late-stage decision queries.
ICP-matched prompt testing. Generic AI visibility testing is not enough for B2B. Your audit needs to test the exact language your ideal customer profile uses, which varies by industry, company size, and buyer role.
Technical buying committees. Content optimized for AI search needs to address the technical buyer, the business buyer, and the executive sponsor - each searching with different queries, each deserving a citation of your brand.
An AI SEO audit is not a vanity exercise. Every gap it surfaces represents a buyer query where a competitor is being recommended and your brand is not. Fixing those gaps does not just improve rankings - it puts your brand into the consideration set of buyers who have already decided to act.
When a buyer asks ChatGPT or Perplexity to recommend a vendor, the response carries a different quality of trust than a sponsored result. An AI SEO audit tells you exactly which queries should be returning your brand - and are not.
In AI search, the trust decision happens before your site is ever visited. An AI visibility audit maps every pre-click touchpoint where your brand should be present and currently is not.
A buyer searching for an AI SEO agency for SaaS companies is evaluating. The audit identifies your highest-value, highest-intent prompt categories where a citation can translate directly to a qualified conversation.
Content restructured for AEO, schema markup, and entity signals keep compounding after implementation. A single audit creates a roadmap whose lead generation value accumulates over time.
The businesses capturing the most AI-sourced pipeline in 2026 are not necessarily the biggest or best-funded. They are the ones whose content is best structured, most authoritative, and most visible to the AI systems their buyers use every day.
This is not a generic automated report. Every audit is researched and written by the Nagana Media team. Here is exactly what it covers.
Your brand's current citation presence across ChatGPT, Perplexity, Google AI Mode, Claude, and Gemini. Delivered as a platform-by-platform table.
The three to five competitors most frequently cited in your category, including which assets, domains, and content formats are driving their visibility.
An assessment of server-side rendering, page speed, robots.txt, sitemap completeness, llms.txt presence, Core Web Vitals, and JavaScript rendering issues.
A complete review of structured data implementation, missing schema types, schema errors, and how well-defined your brand is as an entity.
An AEO readiness review of your top pages: heading hierarchy, answer-first paragraphs, definition blocks, FAQ sections, internal linking, and topical gaps.
Author attribution, author schema, external citation sources, domain authority, backlink relevance, and topical authority signals across your content cluster.
A prioritized action plan tagged by effort, impact, and responsible party so the highest-impact, lowest-effort items come first.
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