When AI writes the answer, it should cite you.
Generative engines don’t return a page of links — they return a paragraph, assembled from a handful of sources the reader never sees. Generative Engine Optimization is the work of becoming one of those sources: a brand the model can identify without ambiguity, retrieve without friction, and quote without hedging. We engineer the entity, the corpus and the evidence, then track what the engines actually say back.
Models don’t rank pages. They choose sources.
A generative answer is built in two moves. First retrieval: the engine pulls a small set of passages it believes are relevant and trustworthy. Then grounding: it writes prose constrained by those passages and attaches citations. Nothing outside that retrieved set exists. Ranking fourth on a results page is irrelevant to a model that grounds its answer in three documents and names two of them.
What decides membership in that set is not keyword density — it is whether a machine can resolve who you are. Entity disambiguation is the gate. If your company name collides with a software product, a US franchise and a defunct agency, retrieval hedges, the model generalises, and your competitor with a clean Wikidata record and consistent sameAs links gets named instead. Add conflicting facts across your site, your LinkedIn, your directory listings and your press coverage, and you have taught the engines that your own claims are unreliable.
Then there is access. Answers are assembled from documents that were crawled and parsed — by GPTBot, PerplexityBot, ClaudeBot, Google-Extended and their successors. A blanket robots.txt disallow, client-side rendering that hides your copy from a non-JavaScript fetch, or a paragraph that buries its claim behind three sentences of preamble all produce the same outcome: no quotable passage, no citation, no mention. GEO closes each of those gaps deliberately rather than hoping the model figures it out.
“Being crawled is not being cited. The model has to know who you are, reach your text, and find a sentence worth quoting.”
The mechanics of getting quoted.
GEO is not a content package. It is entity engineering, access engineering and evidence engineering, run against a benchmark that tells us whether any of it moved.
Entity & knowledge-graph engineering
Organization schema, sameAs links and Wikidata-grade consistency, so retrieval resolves your brand to one unambiguous entity every time.
AI citation tracking
A standing benchmark of what ChatGPT, Perplexity, Gemini and AI Overviews say about you — by prompt, by competitor, by week.
AI-crawler readiness
GPTBot, PerplexityBot, ClaudeBot and Google-Extended access audited end to end: robots.txt posture, llms.txt, server-rendered HTML.
Source-grade content
Original data, dated claims and attributable statistics, written as passages a model can lift verbatim without softening them.
Off-domain corpus presence
We map the third-party sources engines actually retrieve — trade press, roundups, directories, forums — and earn you into them.
Fact reconciliation
One canonical version of your name, location, founding year, pricing model and service list, aligned across every surface a model reads.
Benchmark, then engineer.
Citation baseline
We build a prompt set from how your buyers actually ask, run it across ChatGPT, Perplexity, Gemini and AI Overviews, and record who gets cited today — you, your competitors, or nobody. That file is the scoreboard for everything after it.
Entity & access audit
We trace how the open web describes your brand, find every conflicting or ambiguous fact, and test what an AI crawler actually receives when it fetches your pages without JavaScript.
Build the source
Schema and sameAs corrections ship, the crawler posture is fixed, and we write the quotable assets — original data, clear definitional claims, statistics with a date and a method attached.
Re-run and widen
The prompt set runs again on a fixed cadence. Where citations land we deepen the corpus; where they don’t we diagnose whether the block is entity, access or evidence, and act on that specific cause.
Measured in mentions, not impressions.
Aggregate figures across Digital Bureau accounts, measured against each client’s own baseline prompt set. Results vary by category, competitive density and the strength of your existing corpus.
GEO, answered.
The questions we get asked in every first call about generative engines — answered plainly.
What is Generative Engine Optimization?+
Generative Engine Optimization is the practice of getting your brand retrieved and cited inside answers written by generative AI systems such as ChatGPT, Perplexity, Gemini and Google AI Overviews. Instead of competing for a position on a results page, you are competing to be one of the few sources a model grounds its answer in. The work centres on entity clarity, crawler access, factual consistency across the open web, and content written in passages a model can quote directly.
How is GEO different from AEO?+
GEO is about being the trusted source a generative model cites when it writes an answer. AEO is about being the direct answer to a specific question across every answer surface, including featured snippets, People Also Ask, voice assistants and AI Overviews. GEO asks whether the engine knows and trusts you well enough to name you; AEO asks whether your content resolves the question cleanly enough to be selected. Most brands need both, and we run them off one shared foundation.
How do you actually measure AI citations?+
We build a prompt set that mirrors how your buyers ask — category questions, comparison questions, brand questions, problem questions — and run it on a fixed cadence across the major engines. Each run records whether your brand appears, whether it is cited with a link, which page was used, and which competitors were named alongside you. That gives a share-of-answer trend line rather than a snapshot, so we can tell whether a change we shipped is what moved it.
How long before an AI engine starts citing us?+
The median across our accounts is about 45 days to a first tracked citation, though the range is wide. Access and schema fixes can register within days once the relevant crawlers return. Entity corrections that depend on third-party sources — a corrected directory record, a knowledge base entry, coverage on a site the engines already trust — move on the slower clock of those sources being recrawled. Competitive categories with entrenched incumbents take longer than emerging ones.
Find out what the engines say about you right now.
We’ll run a live prompt set across ChatGPT, Perplexity, Gemini and AI Overviews, show you who gets cited in your category today, and name the specific reason it isn’t you.