What AEO actually is.
Generative answer engines — Google's AI Overviews and AI Mode, ChatGPT search, Perplexity, Gemini, Microsoft Copilot, and the assistants embedded in browsers, phones and cars — run a retrieval-augmented generation loop. They decompose a prompt into sub-queries, retrieve candidate documents, chunk them into passages, score those passages for relevance and trust, and condition a language model on the winners to write a grounded answer with attributions.
AEO engineers your presence at every stage of that loop. We make sure your content is reachable by the crawlers these systems use, rendered without client-side dependencies, segmented into passages that survive chunking intact, written with the definitional clarity and information gain that re-rankers reward, and reinforced by an entity graph that lets the model resolve "you" unambiguously across the open web.
It also extends beyond your domain. Models weight corroboration: a claim that appears consistently across independent, authoritative sources is safer to ground on than one that appears only on your site. So AEO includes deliberate off-site work — knowledge-base reconciliation, structured listings, expert commentary and earned coverage — that turns your claims into consensus.
SEO is necessary. It is no longer sufficient.
Most answer engines still retrieve from a search index, so crawlability, indexation and canonical authority remain the entry ticket. We treat classic SEO as a subset of AEO: the layer that gets you into the candidate set. Everything that decides whether you are quoted happens after that.
Crawl budget and indexation hygiene · canonicalization and duplication control · internal link topology · page experience and Core Web Vitals · authority signals from earned links · keyword-to-intent alignment.
Passage extractability and chunk integrity · entity salience and sameAs reconciliation · information gain over the consensus corpus · cross-source corroboration · AI user-agent governance · prompt-space coverage and citation telemetry.
How an answer engine chooses its sources.
Implementations differ by vendor and change often, but the architecture is converging. We engineer for each stage, and we re-test whenever a major model or ranking update ships.
Query understanding & fan-out
The prompt is classified for intent and decomposed into parallel sub-queries that probe definitions, comparisons, specs and reviews.
We engineer: coverage of the full sub-query space, not just the head term.
Hybrid retrieval
Lexical (BM25-style) and dense vector retrieval pull candidate documents from the index and live fetches.
We engineer: indexability, render parity and vocabulary that matches both sparse and semantic matching.
Chunking & re-ranking
Documents are split into passages; cross-encoders and trust signals re-order them by relevance, authority and freshness.
We engineer: self-contained passages with explicit subjects, claims and evidence.
Grounded synthesis
The model writes an answer conditioned on top passages, preferring claims that are corroborated across sources.
We engineer: consistent facts across your site, knowledge bases and third parties.
Attribution
Spans of the answer are linked back to the passages that supported them — the citation and the click.
We engineer: quotable, attributable statements that map cleanly to your URLs.
Eight signals we engineer — deliberately.
What an AEO engagement ships.
Scoped to your category and competitive density. Every engagement begins with measurement, so improvement is provable rather than anecdotal.
AI visibility audit
Prompt-set sampling across major answer engines; cited-source logging; citation share, inclusion rate and description accuracy versus named competitors.
Prompt-space & fan-out mapping
A taxonomy of the conversational prompts and sub-queries that matter to revenue, clustered by intent and journey stage.
Passage-level content engineering
Rewrites and net-new reference pages structured for chunk integrity: definitional leads, comparison tables, specs, FAQs and evidence blocks.
Entity optimization
Knowledge-graph reconciliation, Wikidata and authority-profile alignment, consistent attributes across listings and directories.
Technical SEO · the subset
Crawl and index diagnostics, canonical strategy, internal linking, Core Web Vitals and render-parity fixes that keep you in the candidate set.
Corroboration & digital PR
Expert commentary, research placements and listings that make your positioning a multi-source consensus.
Citation telemetry
Ongoing prompt tracking, AI referral segmentation in analytics and model-update alerts, reported against business outcomes.
AEO, GEO, SEO — untangled.
Answer Engine Optimization. The umbrella discipline: earning inclusion and citation in any system that returns an answer rather than a list — generative search, assistants, voice and agents.
Generative Engine Optimization. A term often used for the LLM-specific slice of AEO — how content is represented inside generated responses. We treat it as part of the same practice.
Search Engine Optimization. Ranking documents in a traditional index. Still foundational — it governs whether you're retrievable at all — and fully contained within our AEO practice.