Get cited
where buyers
now ask
questions.

We engineer your brand’s presence inside AI-generated answers. That means we audit how AI engines currently describe you, fix the gaps in your entity identity and website structure, build authoritative third-party references through PR and content distribution, and measure answer-share across priority prompts every week. The work runs as a retainer because AI visibility is not a one-time fix — it compounds over time as evidence layers build up.

SEO optimizes for ranking position in a list of links. AI visibility optimizes for whether your brand appears inside the answer itself — as a recommendation, a citation, a named entity in a summary. The signals that drive those two outcomes are different. AI engines rely on entity clarity, corroborating third-party sources, structured content, and confidence signals across the open web. A brand can rank well on Google and be completely absent from AI-generated answers. We focus on the second problem specifically.

We test a defined set of priority prompts across selected AI engines every week and record brand mentions, competitor mentions, citation URLs, sentiment, and position in the answer. We baseline this at the start of the engagement, so every subsequent report shows movement against that starting point. We track which engines are improving, which prompts are still weak, and which sources are being cited. Reports go to the client on a regular cadence.

We start with a baseline AI visibility audit. We test 40 or more priority prompts across 8 AI engines and document where the brand appears, where it does not, what competitors are being recommended, and which sources the engines are drawing from. From that audit, we build an evidence and entity map: what AI systems currently understand about the brand, and what is missing or incorrect. By the end of the first month you have a clear picture of your current AI answer-share and a prioritized list of what needs to change.

Technical fixes and content changes that are already indexed can begin moving answer-share within weeks. Authority distribution through PR and third-party references typically takes 60 to 90 days to influence AI retrieval, depending on the engine and the source. Our internal data shows an average 4.2x citation lift within 90 days for active engagements. The pace depends on how competitive your category is, how established your current evidence base is, and how quickly we can build new corroborating references.

We track ChatGPT, Claude, Perplexity, Gemini, Copilot, Google AI Overviews, You.com, Grok, and Meta AI. The specific engines we prioritize for a given client depend on where their buyers are most active and which engines are most influential in their category.

At minimum: a clear description of what your brand does, who you serve, and what prompts your ideal buyers are likely to ask AI systems. We also need access to your website for technical review, and a list of competitors you are most concerned about. Everything else — the audit, the entity map, the prompt set, the content and distribution plan — we build. You do not need to have existing AEO infrastructure or prior AI visibility work for us to start.

We are designed to run with minimal internal resource from the client side. You will need one point of contact who can review and approve content, answer questions about brand positioning, and sign off on PR assets before distribution. A 60 to 90 minute onboarding call at the start, then a monthly review call. Day-to-day execution — auditing, writing, outreach, monitoring, reporting — sits with us. If your team wants to be more involved in strategy or content direction, we can accommodate that, but it is not a requirement.

No. AI engines are probabilistic, their retrieval behavior changes over time, and no agency can force a citation into a generated answer. What we can do is build the evidence, entity clarity, and authority signals that make your brand the most credible and retrievable option for the prompts that matter to your business. We measure progress through answer-share movement, citation quality, and representation accuracy — not through promises we cannot keep.

Answer Engine Optimization is the practice of making a brand more likely to appear in direct answers, summaries, recommendations, and AI-generated responses. It focuses on answer eligibility, entity clarity, content structure, and trusted evidence that AI engines can retrieve and cite.

Generative Engine Optimization is the practice of improving how generative AI systems discover, understand, cite, and describe a brand across prompts and answer contexts. It focuses on the retrieval layer — making sure the right information about a brand reaches the model and is used accurately in generated responses.

SEO is about ranking in a list of links when someone searches. AEO is about becoming the answer when someone asks. The technical work overlaps in places — structured data, site speed, content quality — but the strategic goal is different. SEO targets click-through from a results page. AEO targets inclusion in the answer itself, where there is no list and often no click required. Brands that rely only on SEO are optimizing for a channel that is shrinking in share of buyer attention.