AI-generated answers are becoming a more visible part of how people research products, services and questions across search and conversational platforms. Search journeys increasingly span traditional search engines, AI-generated search experiences and conversational assistants. We help brands stay visible, accurately represented and citable across all of them — through coordinated SEO, GEO, entity clarity, source authority and AI visibility measurement.
AI search optimization is the coordinated practice of improving how a brand is discovered, understood, represented and referenced across the full range of AI-influenced search experiences — not a single technique or a single platform.
It sits above four more specific disciplines, each of which solves a narrower problem. This page explains how they fit together and points you to the dedicated page for each one. If you already know which piece you need, use the links below; if you need the full picture first, keep reading.
Generative-search systems don't "read the internet" at the moment you ask a question. They rely on a pipeline that discovers, retrieves, and selects sources before a language model generates an answer — and a brand's visibility depends on being usable at each stage.
Our work maps to each stage: SEO and crawlability support discovery, content and entity work support retrieval and selection, and source-authority work increases the odds of being the passage a system actually uses. No stage can be skipped — a page that isn't discoverable can't be retrieved, and a page that's retrievable but unclear is unlikely to be selected.
Google AI Overviews, ChatGPT search, Perplexity, Gemini and Copilot pull from different indexes, weigh sources differently, and refresh at different rates. A brand can appear consistently on one platform and be absent on another — that is expected, not a failure of the work.
Leans on Google's existing web index and ranking signals; strong organic SEO performance is a meaningful input.
Blends live retrieval with model training data; source clarity and third-party corroboration matter.
Retrieval-heavy and citation-forward; favours pages that answer a query directly and concisely.
Draw on their respective ecosystems (Search, Bing); indexation and structured data hygiene still apply.
Because behaviour varies, we test and measure per platform rather than reporting one blended score. See how we measure AI visibility below.
Each specialist discipline has its own dedicated page with full method and detail. This page coordinates them into one strategy; use the links below to go deeper on any one piece.
The coordinating layer — baseline, priorities, and sequencing across the disciplines below.
Hands-on GEO implementation: content structuring, source value and citation readiness.
Applying SEO fundamentals — crawlability, structure, relevance — to AI-influenced search results.
Optimising for how large language models retrieve and interpret content specifically.
Winning direct-answer surfaces — featured snippets, People Also Ask, and AI-generated direct answers.
A structured baseline of where a brand currently appears — and doesn't — across AI search platforms.
AI search visibility is built on the same foundations as organic search visibility, not a replacement for them. Discoverable, well-structured, technically sound pages remain a prerequisite for being retrieved and cited.
We don't treat AI search as a separate track that risks organic performance. SEO foundations are preserved and strengthened first; GEO, entity and authority work builds on top of that base rather than around it.
For dedicated organic SEO work, see our SEO Services page.
AI systems need to resolve who a brand is, what it does, and how it relates to other entities before they can describe it accurately. We improve content structure and implement standard structured data where appropriate to represent visible page information accurately. Structured data can clarify supported entities and attributes, but it does not guarantee generative citation.
Generative systems favour content that is clear, well-sourced and independently corroborated. That depends on firsthand expertise, evidence quality and a maintained body of content — the discipline we call content authority.
A page can be technically perfect and still be passed over if it reads as thin or unsupported. Source value is what makes a page worth citing once it has been retrieved.
AI systems draw on far more than a brand's own website. Third-party mentions, reviews, directories and coverage all feed the pool of material a generative system can pull from and corroborate against.
We map which of these source types already mention a brand, which are missing, and which are realistic to pursue — work that connects to Content Authority and dedicated digital PR.
Before recommending any change, we establish where a brand currently stands across AI search surfaces — using a controlled, repeatable query set rather than a handful of ad hoc prompts.
Generative outputs are probabilistic — the same query can return a different answer on different runs. We test each query multiple times across platforms and report a mention/citation rate, not a single pass/fail result.
A brand's own visibility only means something in context. We identify which competitors are already being cited for the same query set, which sources those answers draw from, and where the gap actually is — content, entity clarity, or third-party presence.
Which competing brands appear across the same controlled query set.
The specific domains and pages generative systems are pulling from.
The clarity, structure or authority signal that made a source usable.
An eight-step framework that runs baseline through iteration, coordinating SEO, GEO, entity and authority work rather than treating them as separate projects.
Run the controlled query set across platforms to record current visibility.
Identify whether gaps are discovery, retrieval, selection or generation problems.
Rank fixes by commercial relevance and effort required.
Improve content clarity, structure and entity signals.
Build third-party presence and earned mentions.
Re-run the query set to check for movement.
Report mention rate, citation rate and share against competitors.
Repeat on a cadence, since platforms and outputs change over time.
We report the specific, verifiable metrics below rather than a single proprietary "AI score" — scores like that can't be independently checked, so we don't use them.
How often the brand appears across repeated test runs.
How often the brand is directly linked or named as a source.
Which domains are cited most often for the target queries.
How often the brand's own pages are among the cited sources.
Visibility relative to named competitors on the same query set.
Performance broken down by category, problem, comparison, recommendation and branded queries.
Whether AI-generated descriptions of the brand are factually correct.
Where analytics can attribute traffic and conversions to AI-referred visits.
Scope depends on current baseline, site size and how many of the underlying disciplines already need work. We size engagements after the baseline audit, not before — so the plan reflects what the data actually shows.
We report AI-search results the same way we measure them: a documented baseline, the work carried out, and a repeated post-work measurement using the same query set. Case studies for this service line are in progress and will be published here with real, verifiable before-and-after numbers as engagements complete.
Original, data-led research is one of the strongest ways to earn genuine third-party citations — both from journalists and from AI systems retrieving evidence-backed claims. We plan and produce original studies as part of digital PR and content authority work rather than relying on recycled statistics.
These terms overlap and are often used loosely. Here is how we define and scope each one.
| Term | Focus | Typical Output | Dedicated Page |
|---|---|---|---|
| AI SEO | Applying core SEO practice to AI-influenced search results | Technical & on-page fixes for AI-era search | AI SEO → |
| GEO | Discoverability, clarity and citation readiness for generative engines | Content & structure optimised for generative retrieval | GEO → |
| LLM SEO | How large language models chunk, retrieve and interpret content | Passage-level structuring for model retrieval | LLM SEO → |
| AEO | Winning direct-answer surfaces (snippets, PAA, AI direct answers) | Answer-formatted content for zero-click surfaces | AEO → |
| AI Search Optimization (this page) | The coordinating strategy across all of the above | Baseline, priorities and sequencing across disciplines | You're on it |
No. GEO is one discipline within AI search optimization, focused specifically on content discoverability and citation readiness for generative engines. AI search optimization is the coordinating strategy that also includes SEO foundations, entity clarity, source authority and measurement.
No. No agency can guarantee a specific generative output, since these systems are probabilistic and platform-controlled. We report mention and citation rates from repeated, controlled testing rather than promising specific placements.
The work is built on top of SEO foundations, not around them. We preserve and strengthen existing organic performance as the base layer before adding GEO, entity and authority work.
No dedicated AI-only markup is required. Clear, well-structured, genuinely useful content and standard structured data where relevant are what generative systems actually use.
The audit is a focused, one-time baseline measurement. This page describes the full ongoing strategy that an audit typically feeds into. You can start with either — many clients begin with the audit.
Timelines vary by starting point, site size and how many source types already reference the brand. We set expectations after the baseline audit rather than promising a fixed number of weeks up front.
We'll identify the AI-search queries that matter for your business, establish a baseline of where you appear today, and show you exactly where the gaps are — before recommending any work.
