AI-SEO
SEO for the AI web, not just the ten blue links.
Our method is built for how people actually find things now — Google and ChatGPT, Perplexity, and Gemini. That means structured, AI-readable pages that models can read, cite, and recommend, plus content engineered to earn a citation instead of blending into the noise.
The real problem
Why the default way falls short.
Optimizing for a web that changed
Classic SEO chases ten blue links, but a growing share of searches now end inside an AI answer that never shows those links. If your site is not structured to be read and cited by models, you are invisible in the channel that is growing fastest.
Generic content earns nothing
Pages that restate what everyone else already says give a model no reason to cite them. Without net-new information — an info-gain angle — content is filler that neither ranks nor gets quoted.
Machines can't read the page
Most sites hand crawlers a soup of unstructured markup with no entity graph, so search engines and LLMs can't reliably tell who you are, what you offer, or why to trust you. Structure is the missing half of SEO.
What you get
- An AI-readable entity graph — one canonical Organization root with cascading Service, WebPage, and Article nodes
- llms.txt and llms-full.txt machine-readable identity files
- FAQPage and Speakable schema so assistants can quote you accurately
- Info-gain content that publishes what competitors leave unsaid
- Local and service-area schema for geo-relevant ranking
- Measurement of both classic rankings and LLM-citation presence — the crawl → cite → click funnel
How a project runs
- 1 · Audit — We map your current structure, schema, and content gaps against how Google and LLMs actually read a site — and against what your competitors do and don't say.
- 2 · Structure — We build the entity graph, structured data, and machine-readable identity files so both crawlers and models can parse who you are.
- 3 · Publish info-gain — We write to the gaps — net-new, specific content that gives a model a reason to cite you, not another restatement.
- 4 · Measure & compound — We track rankings and citation presence together and keep feeding the pages that earn attention. Structured content compounds.
How we think about AI-SEO
The funnel has changed shape. It used to be crawl → rank → click; now, for a large and growing share of queries, it is crawl → cite → click, with an AI answer sitting between the search and the visit. To show up there you have to be legible to the model — a clear entity, backed by structured data, saying something specific enough to be worth quoting. Everything we build is aimed at that.
Structure and content are two halves of one job. An AI-readable entity graph — a single canonical Organization node with Service, WebPage, and FAQ nodes cascading off it — tells a machine who you are and how your pages relate. But structure with nothing to say earns no citation, and great content with no structure can't be parsed. We do both: the graph so you're legible, and info-gain writing so you're worth citing.
Info-gain is the discipline of publishing what your competitors don't. A model has no reason to cite the tenth page repeating the same generic advice; it cites the page that adds a specific fact, a real number, a genuinely useful answer. That is also why we refuse to spin generic doorway pages — they fail the info-gain gate and, increasingly, get demoted for it.
Where it fits
Industries this matters most for.
Questions
AI-SEO FAQ
What is "AI-SEO" and how is it different from regular SEO?
It optimizes for both Google ranking and citation inside AI answers (ChatGPT, Perplexity, Gemini). Alongside classic on-page work, we build an AI-readable entity graph, structured data, and llms.txt so models can read, trust, and quote you — the channel classic SEO ignores.
Can you get my business cited by ChatGPT and Perplexity?
That is the goal of the work: structure your site so assistants can parse it, and publish info-gain content worth quoting. We track citation presence alongside rankings so you can see it working.
What is info-gain content?
Content that adds net-new information the rest of the web isn't saying — a specific fact, number, or answer. It is what earns both rankings and AI citations, and it is the opposite of generic, spun filler.
How do you measure results?
Together: classic rankings and LLM-citation presence, mapped across the crawl → cite → click funnel, so you see both traditional traffic and the AI-answer visibility that traditional tools miss.
Related services
The rest of the stack.
Let's build it
Tell us what you need. We'll scope it clearly and show you exactly what you'll own.