Our approach
From invisible
to cited.
Ahrefs' study of 1,885 pages found brand mentions correlate with AI citations about 3× more strongly than backlinks, while JSON-LD markup had a near-zero (~+2.2%) causal effect. A four-step path, Audit, Build, Deploy, Track, that chases the signals which actually move citations, not the ones that look tidy.
The process
Audit → Build → Deploy → Track.
Four steps from “the AI has never heard of us” to “the AI names us”, each with a measurable output you can check.
Audit
We benchmark your AI visibility across ChatGPT, Claude, Gemini, and Perplexity, and trace where each citation is won, your own page, a directory, Reddit, or a review, since the source differs by engine.
Build
On-site: fact-dense answer blocks, hub-and-spoke topic clusters that build topical authority, and pages readable to AI bots (GPTBot, ClaudeBot, Google-Extended). Off-site: a source map of the directories, Wikidata, and communities each engine actually reads.
Deploy
We ship the on-site fixes and build the off-site footprint across the third-party sources each engine reads, business profiles, the Knowledge Graph, industry directories, and reviews, with one consistent set of entity facts on every listing.
Track
Share of Voice per engine, your named mentions against every competitor's, plus the citation-gap list of exactly who to displace next, reported monthly.
The principle
Specificity is the whole game.
AI retrievers quote the most specific, verifiable passage they can find, and skip generic marketing prose entirely.
When someone asks an assistant “who's the best supplier of X” or “which agency should I hire for Y,” the model retrieves candidate passages and quotes the one that's most concrete: real numbers, named entities, clear claims, and clean structure.
“A provider of quality solutions” gets skipped every time. “Ships 12,000 orders a day to 40 EU retailers” gets quoted, even though both sentences describe the same company. The GEO study (Aggarwal et al., KDD 2024) put numbers on it: adding cited sources raised AI-citation visibility about 40%, statistics about 37%, quotations about 22%. Our method moves your content from the first kind of sentence to the second, and then proves the AI noticed.
What that looks like in practice
We model your business as a clean entity with consistent names, identifiers, and relationships; we make your pages crawlable so AI bots (GPTBot, ClaudeBot, Google-Extended) can read your facts; and we rewrite your highest-value pages to clear the citation bar. Because ranking on Google and Bing reaches roughly 70–75% of AI retrieval surfaces, classic technical SEO still does most of the heavy lifting. Perplexity adds a freshness weight, it discounts pages older than ~90 days and cites content under ~30 days old roughly 3× more often, so we treat publishing cadence as part of the build.
Let's see your baseline.
We'll run the real battery of queries that matter for your business and show you exactly where you stand.
Start with a free audit →