Speak the Language
AI Understands.
Structured data, entity disambiguation, and technical signals that tell AI models exactly what your brand is — and why it’s the right answer.
The technical layer between you and the answer.
AI models don’t just read text — they parse structured data, follow entity graphs, and weight technical signals when deciding what to cite. A technically clean, well-structured site sends the signals that separate cited brands from invisible ones.
Schema markup, entity clarity, and site architecture aren’t optional extras. They’re the foundation that allows AI models to understand who you are, what you do, and whether you’re credible enough to recommend.
How we build it.
Technical Audit
We analyse your current schema markup, identify missing or incorrect structured data, and flag entity disambiguation issues that prevent accurate AI representation.
Schema Implementation
We implement JSON-LD markup for your organisation, products, services, FAQs, and key content types in the formats AI models and Google actually process.
Entity Clarification
We ensure your brand is clearly defined as a distinct entity: consistent NAP data, Wikidata signals, and cross-platform entity alignment that removes ambiguity.
Spotlight shows us exactly what AI sees.
Spotlight’s source analysis examines 47 features of every source AI models cite — including technical signals like schema markup, page authority, and entity clarity. We use this data to identify exactly which technical gaps are preventing your brand from appearing in AI answers.
Ready to appear in AI answers?
Start with a free AI Visibility Audit. We’ll show you your current AI Presence Score and exactly where the gaps are.