GLOSSARY
The AEO & AI search glossary
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) are the practice of getting a brand cited inside AI-generated answers. This glossary defines the concepts, metrics, engines, and tools that make up the AI-search category — each in one plain sentence you can quote.
Core AEO & GEO concepts
The foundational vocabulary of answer engines, AI search, and how brands get cited in generated answers.
Answer Engine Optimization (AEO)
Also: AEO- Answer Engine Optimization (AEO) is the practice of getting a brand cited and recommended inside AI-generated answers, rather than ranking on a traditional search results page.
Generative Engine Optimization (GEO)
Also: GEO- Generative Engine Optimization (GEO) is the discipline of optimizing content and brand signals so generative AI engines surface, mention, and cite you when they compose an answer.
Search Engine Optimization (SEO)
Also: SEO- Search Engine Optimization (SEO) is the practice of improving a page's ranking in traditional search engine results; AEO and GEO extend the same goal to the AI answer layer, where a handful of brands are named instead of ten blue links.
Answer engine
- An answer engine is a system that responds to a query with a direct, synthesized answer — often citing a few sources — instead of returning a ranked list of links.
Generative engine
- A generative engine is an AI system that composes original responses from a large language model, drawing on training data and, increasingly, live web retrieval to ground its answers.
Search engine results page (SERP)
Also: SERP- A search engine results page (SERP) is the page of ranked links and features a search engine returns for a query — the surface AI Overviews and answer engines are increasingly displacing.
Zero-click search
- Zero-click search is a query resolved directly on the results surface — via an AI Overview or answer box — so the user never clicks through to a website, making being named in the answer itself the new win.
AI citation
Also: Citation, Source attribution- An AI citation is the reference an answer engine gives to a source it used, appearing as a linked or named brand within or beneath a generated answer.
Grounding
- Grounding is the process of tying a model's answer to retrieved, verifiable sources so the response reflects current, factual information rather than only the model's training data.
Retrieval-Augmented Generation (RAG)
Also: RAG- Retrieval-Augmented Generation (RAG) is an architecture that fetches relevant documents at query time and feeds them to a language model, so the answer is grounded in external content the model can cite.
Hallucination
- A hallucination is a confident but false or unsupported statement produced by an AI model, which is why grounding and authoritative sources matter for how a brand is described.
Brand mention
- A brand mention is any reference to a company or product inside an AI-generated answer, whether or not it links back — the core unit AEO measurement counts.
Prompt
- A prompt is the natural-language question or instruction a user gives an AI engine; in AEO, tracking which prompts mention your brand is how you find visibility gaps.
Query fan-out
Also: Fan-out- Query fan-out is the technique where an AI engine expands one user question into many related sub-queries, retrieves sources for each, and synthesizes them into a single answer.
Passage (chunk)
Also: Chunk- A passage, or chunk, is a self-contained block of text an answer engine can retrieve and quote independently, which is why writing standalone, citable paragraphs improves AI visibility.
Passage-level citability
- Passage-level citability is how easily a single paragraph can be lifted and quoted by an AI engine on its own — highest when it states its subject, context, and answer in one place.
Large language model (LLM)
Also: LLM- A large language model (LLM) is an AI system trained on vast text to predict and generate language, forming the core of engines like ChatGPT, Gemini, Claude, and Perplexity.
Entity
- An entity is a distinct, recognizable thing — a company, product, person, or concept — that engines resolve and connect in a knowledge graph, so a well-defined brand entity is easier to cite.
Knowledge graph
- A knowledge graph is a structured network of entities and the relationships between them that search and AI engines use to understand and describe brands accurately.
Semantic search
- Semantic search matches a query to content by meaning rather than exact keywords, using embeddings so an engine can retrieve relevant passages even when the wording differs.
Vector embedding
Also: Embedding- A vector embedding is a numerical representation of text that places similar meanings close together in space, letting AI engines retrieve the passages most relevant to a prompt.
Prompt tracking
- Prompt tracking is the practice of running a fixed set of category prompts against AI engines on a schedule to monitor, over time, whether and how a brand is mentioned.
Answer surface
- An answer surface is any place an AI-generated response appears — an AI Overview, a chatbot reply, or an assistant answer — where a brand can be named or omitted.
Conversational search
- Conversational search is the multi-turn, natural-language way people now query AI engines, refining follow-up questions in dialogue rather than typing isolated keywords.
LLM SEO
- LLM SEO is an informal umbrella term for optimizing a brand's presence inside large-language-model answers; it overlaps closely with AEO and GEO.
Epitom's six visibility metrics
The scored metrics Epitom uses to measure how AI engines describe your brand — not just whether you appear, but how.
GEO Visibility
- GEO Visibility measures how often your brand appears in AI-generated responses across engines and query types — the baseline of being present in the answer itself, not just ranking on a page.
Depth
- Depth measures the richness of your brand's presence in AI responses — whether you are a passing reference or a detailed recommendation, since deeper mentions carry more trust and intent.
Sentiment
- Sentiment tracks the tone AI engines use about your brand — recommended, neutral, or cautioned against — so you know whether your citations are working for you or against you.
Position
- Position tracks where your brand appears within an AI-generated answer, because in AI responses word order is trust order — the earlier you appear, the more weight users give you.
Competitive Context
- Competitive Context shows how your brand is positioned relative to others when AI answers the same query — whether you are the primary recommendation, an alternative, or absent.
AI engines & answer surfaces
The generative engines and AI search surfaces where buyers now ask for recommendations.
ChatGPT
- ChatGPT is OpenAI's conversational AI assistant, which answers questions and, with web search, retrieves and cites live sources — one of the most-used answer surfaces for buyers.
Google Gemini
Also: Gemini- Google Gemini is Google's family of AI models and its consumer assistant, generating answers and powering AI features across Google's products.
Google AI Overviews
Also: AI Overviews, SGE- Google AI Overviews are AI-generated summaries shown at the top of Google's results for many queries, citing a few sources and often resolving the question without a click.
Google AI Mode
- Google AI Mode is a conversational, AI-first search experience in Google that answers complex, multi-part queries with a generated response and supporting links.
Perplexity
- Perplexity is an AI answer engine that responds to questions with a synthesized answer and inline citations to the sources it drew from.
Microsoft Copilot
Also: Copilot, Bing Copilot- Microsoft Copilot is Microsoft's AI assistant, built on the Bing index, that generates cited answers across Windows, Edge, and Bing search.
Claude
- Claude is Anthropic's AI assistant, which answers questions conversationally and, with web access, can retrieve and reference current sources.
Grok
- Grok is xAI's conversational AI assistant, integrated with the X platform, that generates answers and can draw on real-time posts and web results.
Meta AI
- Meta AI is Meta's assistant embedded across Facebook, Instagram, WhatsApp, and Messenger, answering questions for a very large consumer audience.
Google Search
- Google Search is the traditional keyword search engine now blending classic results with AI Overviews and AI Mode, making it both an SEO and an AEO surface.
AI crawlers & bots
The user agents AI companies use to crawl, index, and retrieve web content for training and live answers.
GPTBot
- GPTBot is OpenAI's crawler that gathers publicly available web content to help train its models; sites control its access via robots.txt.
OAI-SearchBot
- OAI-SearchBot is OpenAI's crawler used to build the search index that surfaces and links sites within ChatGPT's answers.
ChatGPT-User
- ChatGPT-User is the agent OpenAI uses to fetch a specific page in real time when a ChatGPT user's request requires visiting that URL.
ClaudeBot
- ClaudeBot is Anthropic's web crawler that collects public content used to help train and improve Claude; access is governed by robots.txt.
anthropic-ai
- anthropic-ai is a user-agent token associated with Anthropic's web access, which site owners can allow or disallow in robots.txt.
PerplexityBot
- PerplexityBot is Perplexity's crawler that indexes web pages so they can be retrieved and cited as sources in Perplexity's answers.
Google-Extended
- Google-Extended is a robots.txt token that lets site owners control whether their content is used to train and ground Google's Gemini models, independent of normal Google Search crawling.
Applebot-Extended
- Applebot-Extended is a robots.txt control that lets sites opt out of having content crawled by Applebot used to train Apple's generative models.
Bingbot
- Bingbot is Microsoft's search crawler that builds the Bing index, which in turn feeds Microsoft Copilot's answers and citations.
CCBot
- CCBot is the Common Crawl crawler that builds a large open web dataset widely used to train AI models, making its robots.txt directives relevant to AI visibility.
AEO techniques & signals
The on-site practices and structured signals that make a page easy for AI engines to fetch, parse, and cite.
llms.txt
- llms.txt is a proposed plain-text file at a site's root that gives AI models a curated, Markdown summary of the site's key pages and facts, making a brand easier to represent correctly.
robots.txt (AI directives)
- robots.txt is a root file that tells crawlers — including AI user agents like GPTBot and Google-Extended — which parts of a site they may access, so it governs AI crawlability.
Structured data (JSON-LD)
Also: Schema.org, JSON-LD- Structured data is machine-readable Schema.org markup, usually in JSON-LD, that labels a page's entities and facts so engines can parse and reuse them with confidence.
FAQPage schema
- FAQPage schema is structured markup that pairs questions with answers, giving answer engines clean, self-contained Q&A passages they can lift and cite.
DefinedTerm schema
- DefinedTerm schema is Schema.org markup for a glossary entry — a term and its definition within a DefinedTermSet — that helps engines cite a brand as the source of an industry definition.
Comparison ("vs") pages
- Comparison pages are structured "X vs Y" or "alternatives" pages that answer build-versus-buy questions directly, a format AI engines readily cite when users weigh options.
Newsroom
- A newsroom is a brand-owned hub of product news, launches, and milestones that gives AI engines fresh, authoritative, citable material about a company.
Glossary strategy
- A glossary strategy is publishing clear, structured definitions of industry jargon so AI engines cite your brand whenever those terms come up.
E-E-A-T
- E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness — the quality signals that make content more likely to be trusted and surfaced by search and AI engines.
Content freshness
- Content freshness is how recently a page was published or updated, a signal that raises the odds an AI engine treats it as current and worth citing.
Heading hierarchy
- Heading hierarchy is the logical use of a single H1 and descending H2/H3 headings that lets engines extract a page's structure and summarize the content beneath each heading.
Internal linking
- Internal linking is connecting related pages with descriptive anchor text so crawlers and AI agents can discover, reach, and understand a site's most important content.
Prerendering (SSR for agents)
Also: SSR- Prerendering, or server-side rendering, delivers fully-formed HTML so AI crawlers that do not execute JavaScript can still read a page's real content.
Canonical URL
- A canonical URL is the tag that tells engines which version of a page is authoritative, preventing duplicate-content confusion when they cite it.
Tools & platforms
The category of AI-visibility and AEO platforms — including Epitom and other tools teams use to track AI mentions.
AI visibility platform (AEO tool)
- An AI visibility platform, or AEO tool, is software that measures how often and how favorably a brand appears across AI answer engines and helps teams act on the gaps.
Epitom
- Epitom is a full-stack Answer Engine Optimization platform that tracks brand visibility across 12+ AI answer engines, scores six proprietary metrics, and turns the gaps into an AEO action plan.
Profound
- Profound is an AI visibility platform that helps brands track and analyze how they are mentioned across AI answer engines.
Peec AI
- Peec AI is an AI visibility tool that helps brands and agencies monitor mentions and share of voice across AI answer engines over time.
Otterly.AI
- Otterly.AI is an AI search monitoring tool that tracks brand mentions, links, and sentiment across AI search engines and AI Overviews.
Scrunch AI
- Scrunch AI is a platform for monitoring and optimizing how brands appear across AI search and answer engines.
Ahrefs Brand Radar
- Brand Radar is an Ahrefs feature that tracks how often a brand is mentioned across AI Overviews and AI assistant answers.
Semrush AI Toolkit
- The Semrush AI Toolkit is a Semrush offering that tracks brand visibility and sentiment across AI answer engines such as ChatGPT, Gemini, and Perplexity.
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