GEO: being found and cited by AI answer engines
A growing share of research now ends inside an AI answer. If your expertise is trapped in marketing prose, the model summarises a competitor instead — or describes your business incorrectly.
What is geo — generative engine optimisation?
GEO, or generative engine optimisation, is the practice of structuring content and entity data so AI answer engines can accurately understand, summarise and cite a business.
What it costs you today
- Being described inaccurately, or not at all, in AI answers
- Losing early-stage research traffic that never reaches a search results page
- No control over which facts about the business are repeated
What we do about it
- Clear factual entity descriptions instead of slogans
- Question-first content: direct answer, then explanation, then example
- Extractable structure — definitions, short answers, lists, comparison tables, FAQs
- Consistent structured data so machines resolve the entity confidently
- Original frameworks and first-party data that give a model something to cite
How delivery runs
Answer audit
What do current AI assistants say about the business and its category today.
Entity clean-up
Consistent naming, services, markets and structured data everywhere.
Answer content
Question, direct answer, detail, example, solution, next step.
Recheck
Re-run the same prompts periodically and track how the description changes.
Typical use cases
A specialist business whose category is poorly understood by general models
A brand whose AI-generated description is out of date or wrong
A company entering a market where nobody knows the name yet
Frequently asked questions
It overlaps but is not the same. SEO optimises for a ranked list of links; GEO optimises for being understood, summarised and cited inside a generated answer. Extractability, factual clarity and entity consistency matter more than keyword placement.
Industries where this matters most
Related services
Request a GEO review
Tell us the business and the problem. We come back with what we would build and why — before any commitment.