Generative engine optimization is new enough that the industry is full of confident claims and short on verifiable evidence, and we are not going to add to that. Citation results also move as models are retrained, which means a screenshot proves what happened on one day rather than what the work reliably produces. We publish our own baseline-and-remeasure methodology instead, and will add a client case study only once we have repeated, permissioned before-and-after tracking we can stand behind.
AI SEO: get cited by AI search
Ranking in Google is no longer the whole job. When someone asks an assistant which firm to use, you are either in the answer or you do not exist for that question. We work on the evidence, structure, and citations that decide which.
Measured citation tracking · no ranking guarantees · durable fundamentals

What the work protects
Visibility in answers that never produce a click
Accuracy of what models say about you
Fundamentals that survive the next model update
Evidence status
Proof before promotion.
Signs you are missing from the answer
Generative visibility fails quietly — there is no ranking report that tells you an assistant recommended someone else.
What generative visibility work produces
What changes when your site is structured to be quoted rather than merely crawled.
A baseline of what assistants say today
We record how the major answer engines currently respond to the questions your buyers ask, who they cite, and what they get wrong about you — so there is something concrete to measure against later.
Content shaped to be quoted
Direct answers near the top, specific claims with evidence, clear definitions, and structure that maps to real questions, so a model can extract a passage and attribute it without ambiguity.
Machine-legible facts
Structured data, consistent entity information, explicit authorship, and clean semantic markup mean the details a model needs are stated rather than inferred from something out of date.
Presence in the sources models trust
Answer engines lean on a comparatively narrow set of corroborating sources. Getting your information accurate and consistent across those matters more here than raw backlink volume does.
Tracking that shows whether it worked
Citation monitoring across the major assistants, repeated on a schedule, so the effect of the work is observable rather than asserted.
Baseline, fix, then re-measure
Measure what assistants currently say, fix why, then track whether it moved.
Typical working stack
ChatGPT, Perplexity, and Gemini · Google AI Overviews monitoring · Schema.org structured data · llms.txt · Search Console · Server log analysis for AI crawlers
Measure what the assistants say now
We build a prompt set from the questions your buyers actually ask and record how ChatGPT, Perplexity, and Gemini answer them today — who gets cited, what they say about you, and what is wrong. This baseline is the only honest way to claim an improvement later.
Diagnose why you are absent
Absence has causes: the answer does not exist on your site, it exists but is unextractable, the facts about you are inconsistent across sources, or the site is technically awkward for AI crawlers. Each has a different fix, and guessing wastes the budget.
Make the site quotable
We restructure key content so answers are direct and near the top, add structured data and entity signals, publish machine-readable summaries, and check that AI crawlers can actually reach and parse the pages. This is also good traditional SEO, which is the point — none of it is wasted if the models change.
Re-measure and iterate
The same prompt set is run again on a schedule, so changes in citation and accuracy are observable. Where a fix did not move anything, we say so and try a different explanation rather than reporting the activity as the result.
How the engagement runs
Baseline and citation audit
Weeks 1–2
Diagnosis and content plan
Weeks 2–4
Implementation
Weeks 4–10
Re-measurement cycles
Ongoing, monthly
How quickly citations shift depends on how often the models are refreshed, how much of your category is already well covered by established sources, and how much content genuinely has to be written rather than restructured. Nobody controls model training schedules, so we commit to the method and the measurement, not to a date by which an assistant will name you.
Audit first, then scoped work
We start with a fixed-fee visibility audit that establishes the baseline and the diagnosis, because committing to implementation before knowing why you are absent is how budgets get spent on the wrong fix. Implementation and ongoing tracking are quoted afterwards, in USD, once there is something specific to price. The audit is useful on its own and does not oblige you to continue.
Questions about AI search
What AI SEO actually is, why it matters now, and how it differs from the SEO you already buy.
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What is AI SEO?
AI SEO is the work of making your business visible inside AI-generated answers. It optimizes your content so answer engines — ChatGPT, Perplexity, Google Gemini — cite and recommend you, alongside ranking in traditional results. You will also see it called generative engine optimization, or GEO; they describe the same work.
Related expertise
Find out what the assistants say about you.
Give us the questions your buyers ask. We will show you who gets cited today and what it would take to be in that answer.
Request an AI SEO audit