Websites · Method

GEO architecture, explained.

Seven layers we build into every site so AI engines can reach it, understand it and trust it enough to recommend it.

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The seven layers

What we build, and why each layer matters.

1 · Access

AI engines can only cite what they can fetch. We publish a robots.txt that names each citation crawler (OAI-SearchBot, Claude-SearchBot, PerplexityBot, Googlebot, Applebot), and we check the edge: CDN bot settings often block GPTBot or ClaudeBot without anyone noticing.

2 · The map: llms.txt

A markdown file at the root that tells a language model what the business is in one paragraph, then lists every important page with a one-line description. llms-full.txt adds the services, FAQs and articles in full.

3 · AI discovery files

/.well-known/ai.txt states the usage policy; /ai/summary.json, /ai/faq.json and /ai/service.json give engines the facts in a machine-readable form they do not have to scrape.

4 · One schema graph

A single JSON-LD @graph per page: Organization, WebSite, WebPage, Service, LocalBusiness branches, FAQPage, Person and VideoObject — linked by @id, so the facts never contradict each other.

5 · Freshness and authorship

datePublished and dateModified in the graph, a visible last-updated date, a named author and an RSS feed. Engines prefer sources that show who wrote them and when.

6 · A bilingual entity

English and Arabic pages joined by hreflang, one brand name used consistently, sameAs links to the business's official profiles, and Arabic written natively with dialect search terms.

7 · The gate

No site launches below a GEO score of 80 on the home page and 70 on key pages, with Lighthouse checks and a real-phone pass in both languages. The same check runs again on every release.

Measured, not claimed

Every engagement starts and ends with a score.

We use the open-source GEO Optimizer to score a site from 0 to 100 across nine areas: crawler access, llms.txt, structured data, meta tags, content, freshness signals, AI discovery, brand and entity, and Google AI readiness. The score before the upgrade goes into the proposal; the score after goes onto the case page. See the DejaBrew, Abu Al-Ragheb Tires and Exceed Solutions cases.

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