Engine profiles

The same question, seven different retrievals.

AI tools don't share a fan-out. Each one rewrites, retrieves, and cites on its own logic, which is why one content plan gets uneven results across them. These are the behavior profiles we build libraries against.

Engine retrieval profile

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An engine retrieval profile is a documented model of how one AI tool rewrites a question, which sources it prefers, and what document properties raise a passage's chance of getting quoted. Profiles are what make a question library tool-specific instead of generic.

Why profiles, not averages

An average across seven tools describes none of them.

We make coverage decisions per tool, because the question that wins on Perplexity is often a question Copilot never asks.

ChatGPT

Rewrites hard, then browsesMEASURED

ChatGPT's searches share only about 13% of their words with what you typed, and about 91% of them change between runs of the same question. It favors recent, tightly-structured pages and will quote one passage rather than summarize a whole document.

What to build

Write standalone passages that name your company inside the sentence. A block that depends on the heading above it gets dropped.

Gemini

Knowledge-graph anchoredMODELED

Gemini figures out who you are first and searches against that understanding, so it's unusually sensitive to whether your brand is described the same way across the open web. Contradictory descriptions hurt you more than thin content does.

What to build

Publish one canonical summary of your company and repeat it word-for-word across your own sites, directories, and profiles.

Google AI Mode & AI Overviews

Documented fan-outDETERMINISTIC

Google states outright that AI Mode runs several related searches per question across subtopics and sources. AI Overviews lean on pages that already rank for the smaller question, so classic ranking still gets you into the game.

What to build

Cover the smaller question with a page that can rank normally, then engineer the passage to get quoted.

Perplexity

Citation-firstMEASURED

Perplexity shows its sources and rewards documents that read like references: dated claims, named numbers, explicit comparisons. It cites more sources per answer than any other major tool, which makes it the most winnable surface for a challenger brand.

What to build

Ship comparison tables, dated benchmarks, and methodology notes. Perplexity cites what looks checkable.

Microsoft Copilot

Bing index, light rewritesMODELED

Copilot stays closer to your original wording than ChatGPT and draws on Bing, so Bing coverage gaps turn straight into citation gaps. Enterprise and procurement phrasing survives its rewrites unusually well.

What to build

Make sure Bing indexes you, and write in procurement language: security, compliance, total cost, migration.

Claude

Sparse, high-trustMODELED

Claude searches less often and cites fewer sources, preferring documents with visible reasoning and clear caveats. Marketing superlatives actively backfire; qualified statements are treated as more usable.

What to build

State limits and conditions in the same block as the claim. Hedged, specific writing beats confident copy.

Grok

Real-time social weightingMODELED

Grok weights live discussion far more than the other tools, so practitioner talk about your category moves its answers within days. Owned content alone rarely moves it.

What to build

Seed and join real practitioner threads. This is the one tool where being in the conversation beats publishing.

Next

See your own category fanned out across these tools.