AI search visibility audit

An AI search visibility audit is a one-time check of how suitable your content is for AI systems (ChatGPT, Perplexity, Google AI Overviews, Yandex Neuro and others) to find, understand and cite it in their answers: how well the content answers users' specific questions (rather than just containing keywords), its structure and machine-readability, signals of expertise and trust (authorship, facts, sources — what is often called E-E-A-T), brand mentions and citability online, freshness and completeness, and presence in the sources AI relies on. The goal is to remove barriers and strengthen the factors that increase the chance of appearing in AI answers, and to give a prioritized plan. Honestly about the main point and without hype: this is a new and very fast-changing field, with more reasoned hypotheses than established rules. The audit increases the chances of being noticed by AI, but appearing in their answers, citation or traffic growth cannot be guaranteed: how exactly AI chooses and cites sources is undisclosed, the logic changes literally week by week, and it differs across systems. Moreover, honestly: AI answers sometimes take the click for themselves — the user gets the answer right in the chat and does not visit the site, so "AI visibility" does not always equal traffic and leads. We do not promise to "get you into ChatGPT answers" or "+X traffic from AI". It is a snapshot in time. Part of the check relies on observations and third-party data — these are estimates, not an exact picture of what AI "sees". What you get: a report with barriers and growth points by priority (content, structure, expertise, mentions) and recommendations; implementation and building authority are separate and not quick work. If the site is new, with no content or mentions, we will honestly say you have nothing to show in AI search yet and suggest where to start. Picture this: instead of "we are not in neural-network answers" you learn that your pages do not answer direct questions, the materials have no author or sources, and the brand is barely mentioned on resources AI trusts. The base price starts from 15,000 ₽; it depends on the volume of content.

• AI assistants mention competitors but not you.
• You want to prepare for AI search but it is unclear where to start.
• You have content but do not appear in neural-network answers.
• You see part of your search traffic drop and suspect AI answers.

• Content answerability: does it answer users' specific questions
• Structure and machine-readability of the materials
• Signals of expertise and trust (authorship, facts, sources, E-E-A-T)
• Brand mentions and citability online
• Freshness, completeness and depth of content
• Presence in the sources AI systems rely on
• Comparison with competitors AI already cites
• A prioritized report with barriers, growth points and a plan

• Clear understanding of what stops you from appearing in AI answers
• Priorities: what to work on first
• Recommendations on content, structure, expertise (implementation is separate)
• A sober understanding that these are hypotheses, not guarantees

• We clarify the topic, the audience's key questions and competitors
• We check content answerability, structure, expertise and mentions
• We prepare a prioritized report with a plan and review it with you

• Do you guarantee ChatGPT and other AI will start citing us?

  No. This is a new field where the rules change fast and are not disclosed. The audit increases the chances of being found and cited, but appearing in AI answers or traffic growth cannot be guaranteed — too much depends on closed and changing algorithms.

• Does AI visibility mean more traffic and leads?

  Not always. AI answers sometimes give the user the answer right in the chat, and they do not visit the site. So appearing in AI answers is useful for awareness, but it does not automatically turn into traffic and leads — we account for that honestly.

• How is this different from a DOM audit and a structured-data audit?

  A DOM audit is about the technical HTML structure, a structured-data audit is about Schema.org. An AI visibility audit is broader and about substance: whether the content answers questions, whether there is expertise and mentions, whether you are cited. They complement each other, but they are different services.