AI Visibility / Model Presence (GEO)
Audit and improve how assistants and answer engines describe and cite your brand.
Buyers are asking language models for recommendations, and the models are answering with whatever they have learned about you. Sometimes it is accurate. Sometimes it is out of date or wrong, and sometimes a competitor is cited instead. Generative engine optimisation is the work of making sure your brand is represented correctly and cited when it should be.
The service sits between our AI and marketing practices. It combines an understanding of how models retrieve and cite with the entity, content and structured data work that influences them.
- We measure with a repeatable question set, so improvement is a trend rather than an anecdote.
- The work covers third-party sources, not only your site, because that is where models look.
- Fixes are implemented by our SEO and development teams, so the audit becomes action.
- A global consumer brand whose products are described by assistants using retailer and review-site copy.
- An airline or hotel group losing recommendation queries to aggregators.
- A bank or insurer whose products are compared by assistants using out-of-date terms.
- An assistant describes your brand with information that is wrong or years old.
- Competitors are cited for the questions your buyers ask.
- Marketing has no measurement of how models describe the brand.
- Structured data and entity signals differ across your country sites.
What is included.
- 01
Citation audit
A fixed set of buyer questions run across the major assistants and answer engines, logging how you appear.
- 02
Entity and knowledge review
How your brand, products and people are represented across the sources models learn from and retrieve.
- 03
Structured data and content fixes
Schema, entity consistency, llms.txt and content shaped for citation.
- 04
Source building
Earning presence on the third-party sources assistants rely on for your category.
- 05
Monitoring
Ongoing tracking of citations and descriptions with alerts on changes.
Four steps, no surprises.
- 01
Audit
Baseline of citations, accuracy and competitors across assistants.
- 02
Diagnose
Why models say what they say, traced to sources and gaps.
- 03
Fix
Entity, structured data, content and source work shipped.
- 04
Monitor
Monthly tracking and iteration as models and sources change.
From first meeting to steady state.
- 01Weeks 1 to 3
Audit
Baseline of citations, accuracy and competitors across the major assistants, with a repeatable question set.
- 02Weeks 4 to 10
Diagnose and fix
Sources and gaps traced, then entity, structured data, content and third-party source work shipped.
- 03Month 3 onwards
Monitor
Monthly tracking and iteration as models and sources change.
- Share of assistant answers citing the brand across the fixed question set.
- Accuracy of brand and product descriptions in assistant answers.
- Presence on the third-party sources assistants rely on in your category.
- Referral traffic and conversions from assistants and answer engines.
- GEO lead
- SEO strategist
- Content strategist
- AI engineer
- LLM citation and accuracy audit.
- Entity and source gap analysis.
- Implemented structured data and content fixes.
- Third-party source plan.
- Monthly visibility report.
The audit is a fixed-scope engagement of two to three weeks. Ongoing improvement and monitoring run on a monthly retainer, usually alongside SEO work, with a three-month minimum. Results are measured monthly against the baseline question set.
SEO & AI Search Visibility
Technical, on-page and content SEO extended to answer engines, so people and machines both find you.
MarketingContent & Social Marketing
Editorial, video and social programmes that build an audience and feed search at the same time.
AI Consulting & AutomationCustom LLM & RAG Solutions
Assistants, copilots and knowledge tools grounded in your own documents and data.
AI Visibility / Model Presence (GEO), in plain terms.
Not directly. We influence it through the sources models learn from and retrieve, and we measure the effect. Over time that is a reliable lever.
ChatGPT, Claude, Gemini, Perplexity, Copilot and Google's AI Overviews, adjusted to where your buyers actually ask.
No. It builds on it. Most of the technical foundations overlap, which is why we run the two together.
Retrieval-based assistants can reflect changes within weeks. Descriptions baked into model training take longer. The monthly report separates the two.