An AEO agency built on research, monitoring, and open infrastructure.

Answer Engine Optimization (AEO) is the practice of structuring a website so AI answer engines like ChatGPT, Claude, Gemini, Copilot, and Perplexity can understand, verify, and cite the business when buyers ask for recommendations. It builds on traditional SEO foundations but adds structured data, AI-readable content systems, and entity authority signals that AI models specifically look for when deciding which businesses to surface in conversational answers.

SEO optimizes for ranked search results on Google. AEO optimizes for getting cited by name in conversational AI answers. The underlying fundamentals overlap (quality content, clear structure, real authority), but AEO adds a technical layer of JSON-LD schema, llms.txt files, and entity consistency that helps AI models parse and cite a business directly rather than just rank it in a list of blue links.

Query fan out is a research methodology where a single buyer intent is expanded into hundreds of related prompt variations to map how AI models actually respond across the full landscape. Instead of optimizing for one keyword, AI NYC tests the realistic prompt space buyers use, then tracks which signals on the site move citations across that variation.

We track citation behavior over time using Canonry, our open source agent first AEO operating system, which polls ChatGPT, Claude, Gemini, Copilot, and Perplexity with your target prompts and records whether your business shows up by name. We pair that with @ainyc/aeo-audit technical scoring so you see both the on-page signals improving and the live citation outcomes shifting.

Most engagements start with a free AEO audit on a key page to set a technical baseline. From there we run query fan out research across your buyer prompts, score your full site, identify the gaps that matter most, then either deliver the strategy as a report or implement the structured data, content, and monitoring directly through done for you execution.

No. AI NYC is based in New York City but works with clients nationwide and internationally. Geographic relevance matters for some industries like local services and hospitality, where city level entity signals move citations. For SaaS, professional services, or national brands, the same research driven AEO methodology applies regardless of where the buyer or business sits.

Technical fixes (schema, llms.txt, robots access) take effect immediately for crawlers, but visible citation changes usually take 2 to 8 weeks as AI models index the updates and retrain. Content depth and entity authority work can take longer. We give honest baselines and track results continuously through Canonry rather than promising fixed timelines.

Yes. Both Canonry (the agent first AEO operating system that orchestrates and monitors AI citation work) and @ainyc/aeo-audit (the 13-factor scoring engine) are publicly available on GitHub under permissive licenses. Clients use the exact instrumentation we use internally, and competitors are free to inspect, fork, or build on the methodology.