from GBP 299
AEO Audit
AI visibility check
Technical SEO review
Structured data review
Entity signals review
llms.txt review
Recommendations report
Case study / AI visibility
How mccaigs built its own AI Visibility system
How mccaigs built its own AI Visibility system using Answer Engine Optimisation pages, llms.txt, public assistant knowledge, schema, sitemap coverage, and deterministic assistant answers.
Plain-English strategy
Want your business recommended by ChatGPT, Google AI, and Gemini?
mccaigs treated its own website as a practical AI Visibility project: clarify the entity, explain the services, publish AI-readable knowledge, connect related pages, and keep the deterministic assistant aligned with approved public facts.
The aim was not to guarantee inclusion in ChatGPT, Gemini, Claude, Perplexity, Google AI, or Google AI Overviews. The aim was to make mccaigs easier for visitors, crawlers, and answer engines to understand, cite, and verify.
Case study signals
A practical system of public, crawlable signals.
Public AEO routes
12 connected pages
AI-readable files
llms.txt, llms-full.txt, JSON, Markdown
Assistant model
Static approved knowledge
Promise boundary
No ranking or inclusion guarantees
Service packages
Practical AEO work without promising impossible outcomes.
These packages prepare, optimise, and improve the source material that answer engines may use. They do not guarantee rankings, recommendations, or inclusion in Google AI Overviews.
from GBP 799
AEO Implementation
llms.txt and llms-full.txt
Metadata improvements
Schema improvements
FAQ structure
Internal linking
AI-readable service copy
Sitemap and crawl checks
from GBP 99/month
AI Visibility Management
Monthly AI visibility testing
ChatGPT, Gemini, and Google AI prompt checks
Content recommendations
Schema and content updates
Visibility report
AI Visibility Report
Measure the signals before changing the strategy.
A useful AI visibility report turns uncertainty into a visible checklist. It shows where the business is clear, where answer engines may struggle, and what should be improved next.
01
Overall AI Readiness Score
02
Entity clarity
03
Structured data coverage
04
FAQ coverage
05
AI crawlability
06
llms.txt present
07
ChatGPT visibility
08
Gemini visibility
09
Google AI visibility
010
Recommended next actions
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Read pageCore routes
Follow the complete AEO and AI visibility path.
AEO FAQ
Useful answers before the first conversation.
What did mccaigs build for its own AI visibility?
mccaigs built a static AI visibility system: AEO service pages, AI-readable knowledge files, structured metadata, sitemap and robots coverage, internal links, and deterministic assistant answers from approved knowledge.
Does this guarantee mccaigs will appear in AI answers?
No. It prepares and improves the public signals that answer engines may use, but no one can guarantee inclusion, citations, rankings, or recommendations in ChatGPT, Gemini, Claude, Perplexity, Google AI, or Google AI Overviews.
Can the same approach work for another business?
Yes, if the business has useful public facts to organise. The details change by sector, location, services, proof points, and buyer questions, but the principle is the same: reduce ambiguity and make the business easier to understand.
Can AEO guarantee inclusion in AI answers?
No. No studio can guarantee that ChatGPT, Gemini, Google AI Overviews, or another answer engine will cite a business. The practical aim is to improve the quality, clarity, structure, and crawlability of the signals those systems may use.
How is Answer Engine Optimisation different from SEO?
Traditional SEO helps people find a website in search results. Answer Engine Optimisation helps AI systems understand what the business does, who it serves, why it is credible, and when it may be a relevant recommendation.
Does mccaigs use runtime AI calls for AEO pages?
No. These pages and the supporting site signals are static and deterministic. mccaigs only adds live AI behaviour where it is useful, controlled, and appropriate to the project.
Start a conversation
Bring us the part that should work better.
A useful first conversation can start with a messy workflow, a website that is not pulling its weight, or an AI opportunity that needs a practical route forward.