TL;DR
To compare GEO agencies in the UK, ignore the claims and check five verifiable mechanics on each agency's own website: (1) entity declaration in structured data, (2) presence in the Wikidata knowledge graph, (3) schema depth and correctness, (4) canonical and redirect hygiene, and (5) AI-crawler configuration in robots.txt. An agency that sells GEO but has not done this work on its own site cannot credibly do it for you. Every check below is free and takes minutes.
Every GEO agency says it can make you visible in AI search. Here is how to verify that yourself, in about twenty minutes, using only public tools, before you spend a penny.
The list of UK agencies offering Generative Engine Optimisation has grown faster than almost any category in digital marketing. By late summer 2026 we had counted at least eighteen firms publishing "best GEO agency" comparison lists, and the publisher is often one of the agencies on the list. That is not a criticism. It is simply how the category is being defined right now: the agencies that publish the comparison own the conversation. When we last checked, we were named on none of them.
The problem this creates for a business owner is simple. Nearly every one of these firms makes the same promise, in nearly the same language. "Get cited by ChatGPT." "Appear in Google AI Overviews." "Own your category in generative search." When every provider claims the same outcome, the claim stops being useful information.
So this guide does something different. Instead of ranking agencies, it teaches you how to inspect one, including us. GEO is unusual among marketing disciplines in that most of the important work leaves a public, verifiable trace. You do not need to take an agency's word for whether it understands entity declaration or schema depth. You can look.
We have applied every one of these checks to our own site, and we show you the results, including the parts that are still in progress. That is the honest version of a case study: not a traction story, but a method you can audit.
Why "best GEO agency" lists are a weak way to choose
Comparison lists rank on assertions: years in business, logos, a paragraph of outcomes with no way to check them. In a young category, those assertions are almost impossible to falsify. A firm that started offering GEO six months ago and a firm that has been doing entity work for two years can write identical copy.
The lists are also usually written by the agencies competing in them. A "10 Best GEO Agencies in the UK" page is exactly the kind of structured, citable, question-shaped content AI engines like to quote, so it ranks because it is well optimised, not because it is impartial. This article is a piece of content strategy too, and we would rather say so. As a buyer, understand that a ranking's position tells you about the publisher's optimisation, not about the ranked agencies' competence.
The way out is to stop reading claims and start reading implementations. GEO is a technical discipline whose outputs are public. Use that.
The five verifiable mechanics, and how to check each one yourself
For each mechanic below you will find what it is, why it matters for AI search visibility, how to check it on any agency's site, and what a good result looks like. Run these against any shortlist, including ours at themetavision.co.uk.
1. Entity declaration
What it is. An entity is the way a search or AI system understands what a thing is: a named organisation with defined attributes, distinct from every other similarly named thing. Entity declaration is the structured statement, embedded in a website's code, that says "this business is X, it does Y, it is based in Z, and here are the authoritative records that confirm it."
Why it matters. Generative engines answer questions by resolving entities. When a user asks "who are the AI creative agencies in the UK," the engine is assembling a set of entities it is confident about. If your business is not a well-declared entity, you are not a candidate for the answer, however good your service is.
How to check it. Open the agency's homepage, view the source (right-click, View Page Source), and search the code for application/ld+json. Inside those blocks, look for an Organization (or ProfessionalService) type with a name, a sameAs array, and ideally the company's legal name. The sameAs array is the tell: it should link out to authoritative records such as Wikidata, LinkedIn or Companies House that independently confirm the entity.
What good looks like. A single, clean Organization node; the legal company name present; a sameAs array pointing to at least two authoritative external records; consistent naming between the schema, the visible page and those external records. If an agency selling GEO has no Organization schema at all, it is selling a discipline it has not applied to itself.
Our own result. The Metavision declares Organization and ProfessionalService in a combined graph, states the legal name The Metavision Multimedia Limited in source, and carries a sameAs reference to our Wikidata record (see mechanic 2). We adopted this to fix a real entity-confusion problem, described in the worked example below.
2. Knowledge graph presence (Wikidata)
What it is. Wikidata is the open, structured knowledge base that underpins a large part of how AI systems and search engines check entities. A Wikidata item is a machine-readable record with a stable identifier (a "Q number") stating what your organisation is and linking it to other facts.
Why it matters. When an AI engine needs to confirm that an entity exists and is what it claims to be, a knowledge-graph record is among the strongest signals available. It is external, structured, and independent of your own website.
How to check it. Search the agency's exact name at wikidata.org. If a record exists, check that it is populated: a sensible "instance of" (for example, business), an "official website" linking back to the agency, an inception date, and a coherent description.
What good looks like. A live Wikidata item, correctly typed, with the official website property pointing back to the agency's domain, and the same Q number referenced in the site's Organization sameAs. Site points to Wikidata, Wikidata points to site.
Our own result. The Metavision holds Wikidata item Q138758110, declared in our homepage sameAs, with its official website pointing back to themetavision.co.uk. The loop is closed. The value of a knowledge-graph record scales with how completely and accurately it is populated, and maintaining it is ongoing work, not a one-off tick.
3. Schema depth and correctness
What it is. Schema markup is structured data that labels the content on a page so machines can understand it precisely: that this text is an FAQ, that this is an article with a date, that this is a service. Depth is how much of the page's meaning is marked up; correctness is whether the markup validates and matches what a human sees.
Why it matters. AI engines extract answers from structured content more reliably than from unstructured prose. FAQ, Article and Service markup map onto the shapes AI answers take.
How to check it. Run the agency's key pages through validator.schema.org or Google's Rich Results Test. Look at how many distinct schema types are present, whether they validate without errors, and whether the marked-up content matches the visible content.
What good looks like. Several correct schema types per page where warranted (FAQPage on question-led pages, Article and BreadcrumbList on blog posts, Service on service pages), all validating and all matching the visible content.
Our own result. Our homepage carries Organization, ProfessionalService, WebSite and FAQPage. Our GEO service page adds Service, FAQPage and BreadcrumbList. Our blog posts, including this one, carry Article and BreadcrumbList. They do not yet carry FAQPage markup for their FAQ sections. That is the next piece of work on our list, and you can confirm all of this in the page source.
4. Canonical and redirect hygiene
What it is. Canonicalisation tells search and AI systems which URL is the authoritative version of a piece of content. Redirect hygiene is the correct, permanent (301) routing of old or alternate URLs to their live equivalents, with no dead ends.
Why it matters. Duplicate or ambiguous URLs split the signals that make a page authoritative, and broken links undermine trust. This is unglamorous work, which is why checking it is diagnostic.
How to check it. Spot-check a few pages for a rel="canonical" tag that points to a sensible, self-consistent URL. Try loading an old or alternate path and confirm it redirects to a live page rather than an error. Click through the main navigation and footer for dead links.
What good looks like. Every important page declares a clean self-canonical; alternate paths redirect to their canonical target; internal links resolve; the sitemap lists the live pages and nothing else.
Our own result. We run redirects at the edge, self-canonicals across the site, and a dynamically generated sitemap so new content appears automatically. Every internal link in this article was checked live before it was published.
5. AI-crawler configuration
What it is. The robots.txt file at the root of a domain tells automated crawlers what they may access. That now includes the crawlers behind generative engines: GPTBot (OpenAI), PerplexityBot, ClaudeBot (Anthropic), Google-Extended and others.
Why it matters. If an AI crawler is blocked, the engine behind it cannot read your content and therefore cannot cite you. Many sites block these crawlers by accident, inheriting a default that pre-dates them.
How to check it. Load the agency's /robots.txt directly in your browser. Look for how it treats GPTBot, PerplexityBot, ClaudeBot and Google-Extended: either named rules, or a deliberate allow-all that covers them. A blanket block on AI crawlers on the site of an agency selling AI-search visibility is a contradiction worth asking about.
What good looks like. A robots.txt that makes a clear, intentional decision about AI crawlers, consistent with wanting to be cited, and an agency that can explain why.
Our own result. Our robots.txt allows all crawlers and names most of the major AI crawlers explicitly, including GPTBot, PerplexityBot and Google-Extended. Anthropic's current crawler, ClaudeBot, is covered by the allow-all rather than named. It is permitted either way, and we are adding it by name.
The worked example: an entity-resolution fix on our own domain
The most useful thing we can show you is not a testimonial. It is a problem we had, the mechanics we applied, and the change we measured.
The problem. Earlier in 2026, AI search engines were confusing The Metavision Multimedia Limited with an unrelated company of a similar name, with a separate Companies House registration and a different sector. When users asked AI engines about us, the answers pulled attributes from the wrong entity. This is one of the most damaging GEO failures there is: the engine is confident, and confidently wrong about who you are.
The mechanics we applied. We declared a clean Organization and ProfessionalService entity with the legal name in source. We created and referenced Wikidata item Q138758110 to give the engines an external anchor. We added Article schema and fixed canonicalisation so the correct pages carried unambiguous authority.
The change we measured. Follow-up testing across AI engines showed answers shifting to attribute our services and brand properties to the right entity. On the descriptive long-tail query we track, our own site began to surface as the first-named result, with the other company no longer bleeding into the answer. We did this on our own domain, with no client, using only the public mechanics described above.
That is the honest shape of GEO proof at our stage: a real entity-resolution outcome, the levers that produced it, and a way for you to verify every one of them on our site yourself. We have written separately about how to measure AI search visibility and why entity resolution is only the first of three layers.
A twenty-minute checklist for comparing any GEO agency
Score each mechanic present, partial or absent for every agency on your shortlist.
- Entity declaration: view source, find application/ld+json, and confirm an Organization or ProfessionalService node with the legal name and a sameAs array pointing to authoritative records.
- Wikidata presence: search the agency name at wikidata.org and confirm a populated, correctly typed item whose official website points back to their domain.
- Schema depth: run key pages through validator.schema.org, count the valid schema types, and confirm the markup matches the visible content.
- Canonical and redirect hygiene: check for self-canonical tags, confirm old paths redirect correctly, and click the navigation and footer for dead links.
- AI-crawler configuration: load /robots.txt and confirm a deliberate, visibility-consistent treatment of GPTBot, PerplexityBot, ClaudeBot and Google-Extended.
An agency scoring "present" across all five has applied its own discipline to itself. An agency selling GEO that scores "absent" on entity declaration and schema is asking you to buy work it has not done for its own name.
Rather have a second pair of eyes run these five checks, on your site or on an agency you are considering? That is the diagnostic we do. Talk to us.
FAQ
What is a GEO agency?
A GEO (Generative Engine Optimisation) agency helps businesses become visible in AI-powered search: the answers produced by ChatGPT, Perplexity, Google AI Overviews and similar systems. Where traditional SEO targets ranked links, GEO targets being cited inside the AI-generated answer, largely through entity declaration, structured data and knowledge-graph presence.
How do I choose the best GEO agency in the UK?
Do not choose on claims, because nearly every agency makes the same ones. Verify five public mechanics on each agency's own website: entity declaration, Wikidata presence, schema depth, canonical and redirect hygiene, and AI-crawler configuration. Every check is free and takes about twenty minutes in total.
Can I check a GEO agency's competence myself without technical skills?
Yes. The checks need only a web browser and two free tools, validator.schema.org and wikidata.org. Viewing a page's source and reading a robots.txt file need no coding.
Why does entity declaration matter so much for AI search?
Generative engines answer questions by resolving entities they are confident about, not by matching keywords. If your business is not declared as a clear, consistent, externally verified entity, the engine has no confident way to include you in an answer.
What is the difference between SEO and GEO?
SEO optimises to rank a link higher in a list of results. GEO optimises to be named and cited inside an AI-generated answer, where there is often no list at all. They share technical foundations, but GEO puts far more weight on entity resolution and knowledge-graph signals. We cover this in more depth in GEO vs SEO.
Should a GEO agency have a Wikidata entry?
It is a strong positive signal. A populated, correctly typed Wikidata item gives AI systems an external record to confirm the entity. Its absence is not automatically disqualifying, but its presence, closed-loop with the site's schema, is meaningful evidence of competence.
What proof should I expect from a GEO agency that can't show me client results?
A worked example on its own domain: a problem, the specific mechanics applied to fix it, and the measured change in how AI engines then described the business. Ask for every lever to be checkable in public.
Conclusion
The GEO category is being defined right now, mostly by the agencies confident enough to publish the comparison lists. As a buyer you do not have to accept that framing. GEO's most important work is public and checkable, so the fairest way to compare agencies, including us, is to inspect the five mechanics rather than read the claims. Run the twenty-minute checklist above. If you want a second pair of eyes on what you find, on your own site or on an agency you are considering, that is precisely the diagnostic we do. Assess your own AI visibility first, then talk to someone who can show you their working.