The Citation
Engine.
Most agencies tell you where you show up in AI. We engineer why you get cited, then build the system that makes it compound. The Citation Engine is the repeatable method behind every win, from the most-cited brand in its category to 8-figure ARR.
Why, not just where.
An AI visibility dashboard tells you you're losing. It doesn't tell you what to do about it. The Citation Engine starts from a different question: what makes a model choose one brand over another when it answers a buying question? Answer that, and visibility stops being something you measure and becomes something you manufacture.
Start from how the machine actually decides. Ranking and citation are two different systems: Google asks “is this page relevant?” while the model asks “will I look wrong if I repeat this?” Citation is a risk decision, not a relevance one, the model quotes the sentence that's safest to attribute. So we engineer for that: defensible, self-contained claims the model can lift without hedging.
From there we work backwards from the answer: which prompts drive your category, which sources each model pulls from, what signals make those sources trustworthy, and then we build and earn exactly those signals. It's the same system that made Swydo the most-cited brand against its competitors, with zero outreach.
And we measure it honestly. AI visibility is sampling, not counting, ask “best X” ten times and the answer drifts. So we track citation share as a distribution over time, closer to polling than rank-checking, and report the trend rather than a flattering screenshot.
Diagnose. Build.
Earn. Compound.
Diagnose
We map your category's real buying prompts, generate 20–30 conversational variations of each, and audit how ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews answer them today. We pull 12–18 months of closed-won data so we optimize for the queries that actually convert, not vanity volume. Output: your Answer Map.
Build
We make you machine-legible and worth quoting: schema and entity work, a clean topic-cluster architecture, money-page optimization, and source-worthy content engineered to be the passage an LLM lifts. The same foundation ranks you on Google and makes you retrievable by a model.
Earn
We place you on the exact sources models trust for your category, Reddit, G2, YouTube, authority blogs and listicles, with organic citation building, not bought links. This is the stage most agencies skip, and it's where AI citations are won.
Compound
We track citation share, AI visibility and pipeline attribution week over week, watch for models misrepresenting you, and reinvest in whatever is moving revenue. Authority compounds, the lead widens as competitors wake up.
The inputs that decide the answer.
“Get cited by AI” isn't magic, it's a finite set of signals you can deliberately build. These are the levers the Citation Engine pulls.
Entity clarity
A consistent, structured definition of who you are and what you're best at, so models recognize and recall you as a distinct entity.
Source presence
Coverage on the third-party domains models actually retrieve for your category, the difference between mentioned and invisible.
Retrievability
Crawlable, well-structured, chunk-friendly pages a model can lift cleanly and attribute back to you.
Corroboration
Multiple independent sources telling the same story about your brand, the consensus models reward.
Freshness
Up-to-date pricing, positioning and facts, so the model never recommends a stale or wrong version of you.
Distinct POV
Original data and a real point of view, the content worth quoting, not the generic page a model skips.
A system, not a service menu.
Point the engine
at your category.
Book a strategy call. We'll run Stage 1 live on the call, your Answer Map, free to keep.
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