Everything that turns a brand into a cited source.

AI visibility auditing

An AI visibility audit measures how often, and in what terms, AI answer engines mention your brand across the questions your buyers actually ask. It is the baseline every other decision is made against.

We assemble a prompt set that mirrors real buying questions, run it across ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews, and record three things for each: whether you appear, in what context, and which competitors are named in your place. The output is a scored baseline plus a ranked list of the gaps worth closing first.

Prompt research

Prompt research is the AI-era replacement for keyword research: identifying the natural-language questions that trigger an answer your brand should be part of.

Prompts behave differently from keywords. They are longer, more conversational, and heavy with context and constraints — "best CRM for a 12-person agency that already uses Slack" rather than "best CRM." Engines then fan a single prompt out into several narrower searches and answer from the combination. We map both layers: the prompts your customers type, and the sub-queries the engine generates underneath them, because a citation can be won at either level.

Answer-optimized content

Answer-optimized content is written so a language model can lift a clean, self-contained passage from it and attribute that passage to you.

In practice that means the direct answer sits in the first two sentences rather than after a four-paragraph preamble; headings are phrased as the questions people ask; claims carry specific figures and named sources; and every section stands on its own without the paragraphs around it. The controlled research on this is unusually clear — adding authoritative quotations alone lifted visibility by 30 to 40% in the Princeton and IIT Delhi GEO study, with statistics and citations close behind.

We work on your existing pages before writing new ones. Most sites have pages that already deserve to be cited and simply are not structured to be.

Technical AI SEO

Technical AI SEO makes your site legible to machines: structured data, a coherent entity, and crawl access for the AI agents that matter.

The work covers Schema.org markup (Organization, Service, FAQPage, Product, Article), a consistent entity description repeated identically everywhere your brand appears, an llms.txt file describing your site to language models, explicit crawler policy for GPTBot, ClaudeBot, PerplexityBot and Google-Extended, plus the conventional foundations — clean information architecture, fast pages, correct canonicals and an accurate sitemap.

Authority & citation building

AI engines trust what the wider web says about you more than what you say about yourself, so a large share of AEO happens off your own domain.

We pursue mentions in the source types these models lean on: industry publications, credible directories and comparison sites, expert roundups, community discussion, and reference pages. Consistency matters as much as volume — the same entity name, the same description, the same category claim everywhere, so the model resolves every mention to one confident picture of who you are.

AI citation tracking

Citation tracking re-runs your prompt set on a schedule and logs every mention, turning AI visibility from an anecdote into a measurable trend.

Spot-checking ChatGPT by hand is not measurement — answers vary between runs, so a single query proves nothing either way. We query the engines programmatically on a fixed cadence with a fixed prompt set, log citation rate, share of voice against named competitors, and sentiment, then report the trend. That is also what makes the work accountable: you can see whether last month's changes moved anything.