When AI answers the question, be the source it cites
A growing share of discovery now happens inside AI interfaces — ChatGPT, Google AI Overviews, Perplexity and Gemini. They don't rank pages; they retrieve, synthesise and cite the sources they trust. Generative Engine Optimisation makes your brand one of those sources.
What AI search is, and why it isn't ranking pages
For two decades, search meant a ranked list of ten blue links. You optimised to climb that list. AI search works differently: a language model reads across many sources, decides which it considers credible, and writes a single synthesised answer that cites only a handful of them.
The competition is no longer for position three versus position four. It's binary — either the model trusts you enough to cite, or it doesn't mention you at all. Optimising for that outcome is a different discipline, and it's the one reshaping discovery fastest.
Traditional search
- close Ten ranked links per query
- close User picks where to click
- close Position is gradual — 1st vs 5th
- close Optimise to climb the list
AI search
- check_circle One synthesised answer
- check_circle Model picks what to cite
- check_circle Visibility is binary — cited or invisible
- check_circle Optimise to be trusted as a source
How AI systems decide what to cite
Citation isn't random. Retrieval systems consistently favour sources that demonstrate five things. We engineer all five.
Topical depth
AI systems prefer sources that cover a topic comprehensively. Complete coverage of a subject raises citation probability across the full query space, not just one question.
Entity clarity
Unambiguous signals about who you are, what you do and what you sell improve knowledge-graph confidence — the difference between being understood and being skipped.
Structured data
Well-formed schema lets retrieval systems extract and trust specific facts — entities, relationships, definitions — rather than guessing at them from prose.
Reference network
Being cited by authoritative sources signals trustworthiness. The same editorial credibility that earns rankings earns citations in AI-generated answers.
Direct answers
Content formatted as clear, complete responses to specific questions is more accurately retrievable — and far more likely to be quoted without misrepresentation.
What a GEO engagement delivers
Retrieval Optimisation
Structuring content for how language models retrieve and synthesise: direct answers, clear entity relationships and unambiguous source attribution.
Knowledge Graph Presence
Entity disambiguation across Google's Knowledge Graph so your organisation, people and products are correctly and completely represented.
Schema for AI Pipelines
Markup that feeds both search indexers and AI retrieval systems: Organisation, Person, Product, Article, FAQ and HowTo, correctly deployed and tested.
Answer-Engine Formatting
Direct-answer structures, clear definitions and formatted summaries that AI systems can extract and cite without distorting your meaning.
Topical Comprehensiveness
Complete topical coverage that signals genuine authority — the single strongest lever on how often you are cited across a topic.
AI Citation Tracking
Ongoing measurement of where and how often you surface across AI interfaces, so visibility becomes something you can see and improve.
Discovery, structuring, measurement
A clear sequence: understand how AI answers your topic today, restructure so it can cite you, then measure citations and improve.
Discovery
Weeks 1–2We map the questions your buyers ask AI systems, how those systems currently answer them, and which sources they cite. This is the baseline: where you appear today and where competitors are being quoted instead of you.
Structuring
Weeks 2–6We resolve entity ambiguity, deploy schema for retrieval, reformat content into extractable direct answers and close topical gaps. The work that makes your pages legible to retrieval systems, not just to crawlers.
Measurement
OngoingWe track citations across ChatGPT, Google AI Overviews, Perplexity and Gemini, watch how your share of cited answers grows, and feed what we learn back into the next round of structuring.
AI visibility, answered
What is Generative Engine Optimisation (GEO)? expand_more
GEO is the practice of structuring your content, entities and data so AI search systems retrieve and cite you when they generate answers. Where traditional SEO optimises for a ranked list of links, GEO optimises for being the source an AI interface trusts to quote for your topic.
How is AI search different from ranking pages? expand_more
Traditional search returns ten links and lets the user choose. AI search reads across sources, synthesises a single answer and cites a small number of them. You are no longer competing for a ranking position — you are competing to be one of the few sources the model considers authoritative enough to reference.
Which AI systems does this cover? expand_more
The major generative interfaces people now use for discovery: Google AI Overviews, ChatGPT search, Perplexity and Gemini. The underlying inputs — entity clarity, structured data, topical depth and credible references — drive citation across all of them.
Do I still need traditional SEO? expand_more
Yes. The inputs overlap heavily: authoritative content, structured data and topical depth drive both rankings and citations. GEO adds layers on top — entity disambiguation, answer formatting and retrieval-ready structure. We treat them as one connected system rather than competing priorities.
Can you actually measure AI visibility? expand_more
We track how often and where you are cited across the major AI interfaces for your target queries, establish a baseline before any work begins, and report movement over time. It will never be as precise as rank tracking, but the trend is measurable and we are transparent about how we measure it.
See how AI search answers for your topic
Book a free consultation. We'll show you who AI systems currently cite for your key questions — and what it would take to put your brand among them.