Get cited on every AI engine that matters

Why engine-specific AEO matters

Not all AI engines are built the same. ChatGPT pulls from a mix of training data and real-time web retrieval via Bing. Perplexity runs live search across multiple indexes and cites inline sources. Gemini leans on Google's Knowledge Graph and Search index. Claude relies heavily on training-time authority signals. Microsoft Copilot fuses Bing ranking with GPT-4 generation. Google AI Overview synthesizes answers directly inside the search results page, pulling from whatever Google already ranks.

Each of these engines has distinct retrieval mechanisms, citation patterns, and ranking signals. A page that gets cited in Perplexity answers may never appear in a ChatGPT response, and a brand that dominates Google AI Overviews might be invisible in Claude. The structural markup, content format, and authority signals that trigger a citation vary engine by engine. A blanket “AI optimization” strategy that ignores these differences leaves gaps where competitors get cited instead.

This is what makes engine-level visibility tracking non-negotiable. You need to know not just whether AI engines mention your brand, but which engines cite you, for which queries, and how often. A SaaS company might have strong citation rates in ChatGPT for product comparison queries but zero presence in Perplexity for the same terms. Without per-engine data, you are optimizing blind.

GetCited monitors 10 AI engines simultaneously, tracking citation rate per query per engine on a recurring schedule. Every engine gets its own playbook below, covering how it retrieves information, what content signals it prioritizes, and what specific gaps GetCited's audit checks for. Pick the engine you want to win on, or work through all of them.