Who are the best GEO agencies in the UK?

Buried has four case studies that name AI visibility. Three include a figure, with the client and period stated. One compares performance before and after against a named competitor. The figures do not identify their source, which limits how easily a buyer can verify them.

Buried has the clearest measurement approach in the study. It covers eight indicators, three named tools, a stated reporting rhythm and six answer engines. The reporting also connects visibility with leads and sales, giving buyers a clearer view of commercial impact.

Buried has a perfect average across the available reviews. It is the only agency with a readable client review that specifically names GEO work, and the reviews are recent.

Buried covers the widest range of GEO subjects in the study. Its published work includes two original data studies with named authors and reviewers. The datasets measure AI interest by city, so they sit somewhat apart from how generative search itself behaves.

Buried appears in the tracked AI answers more often than most agencies. That places it near the top of the field for its own visibility.

Buried publishes a team with AI-search expertise. LinkedIn shows roles centred on both GEO & SEO. We also checked the company's external record.

Buried publishes GEO pricing in tiers, matched to buyer size and itemised by deliverable. The site does not publish a minimum term or notice period, so you would need to ask about those before appointing the agency.

Clickslice publishes four dedicated answer-engine case studies. They name the clients and show where visibility and citation share started and finished. The fourth covers Clickslice's own brand, which the agency discloses. None gives a measurement period.

Clickslice names its measurement instrument and builds prompt sets for individual clients. Clients get live dashboards, with reporting that extends through to leads, sales and revenue. That gives buyers a useful line from AI visibility to commercial results.

Clickslice has the highest review count in the study, with a strong and recent average. The readable reviews cover search work, with two describing the sales process before the work began.

Clickslice covers a broad range of AI-search subjects and publishes two calculators. Its strongest material takes a clear position on measuring visibility. Much of the remaining AI content consists of agency rankings, and the agency publishes no original dataset analysis.

Clickslice appears in the tracked AI answers more often than most agencies. It sits in the upper part of the field for its own AI visibility.

One LinkedIn role carries the AI-search discipline directly. An agency-of-the-year win and vendor partner accreditation add external evidence, alongside the company's record.

Clickslice publishes a starting monthly figure and an itemised link-building rate card. Its AI-search pages do not give a specific price, and no minimum term is published.

SEO Works has five pieces of client work that name AI visibility, the most in the study. The strongest names the client and period, then tracks the result through to revenue. None gives a starting point or names the measurement instrument, so the change is harder to check.

SEO Works explains what it tracks, states that reporting is monthly and builds the work around client targets. Its case studies connect AI visibility with conversions and revenue. The agency does not name the tools used.

SEO Works has a solid average across a large number of reviews. Two readable reviews specifically mention search work and are recent. There is also a noticeable tail of one-star reviews, which deserves a closer look before you appoint the agency.

SEO Works has a substantial dataset library, including research with clearly stated sourcing and sample limitations. Some of its strongest work focuses on SEO and brand rather than generative search itself.

SEO Works appears in the tracked AI answers more often than almost any other agency in the study. It ranks second on this measure.

SEO Works has an established team and external evidence of its reputation. Its published material gives less specific evidence about dedicated AI-search roles, so ask who would handle that work day to day.

SEO Works publishes four pricing tiers, with figures and an explanation of who each tier suits. Five pieces of client AI-search work provide further evidence of the service.

Exposure Ninja has ten case studies that mention AI visibility, including three with a figure. The strongest names the client, states the period and tracks AI Overview presence and ChatGPT traffic through to conversions. None names the source of the figures, so a buyer cannot fully check them.

Exposure Ninja explains what its audit assesses across five named platforms, and clients receive the full prompt library. The agency does not name a measurement instrument or give a reporting rhythm for the AI work.

Exposure Ninja has a very large number of recent reviews with a strong average. The readable reviews cover search and website work, although none specifically mentions AI search.

One report provides original analysis with a stated method. It counts which brands AI answers cite within a sector. The report does not give the sample size, and two further reports sit behind download forms.

Exposure Ninja appears only occasionally in the tracked AI answers. That puts it in the lower half of the field for its own AI visibility.

Two formal job titles carry AI-search responsibilities. The chief executive speaks at major industry conferences, while an agency-of-the-year title and a long list of award shortlists add external evidence.

Exposure Ninja publishes no price for its own services. An outside register carries a rate, while the agency itself has argued publicly that businesses should publish pricing. Buyers will need to ask for a proposal before they can judge the cost.

Impression publishes one AI-search case study with unusually detailed evidence. It names the client, states a 12-month period, explains the tactics and sources the figures to the tools behind them. It does not give the starting position, so the scale of change remains difficult to judge.

Impression names three measurements and tracks prompts by topic and business. Reporting reaches conversion and revenue. The agency describes its tracking software but does not name it, and it gives no reporting rhythm.

Impression has a strong average across a good number of reviews. One mentions search work, while the others are more general. The newest readable review is around a year old.

Impression covers eight distinct AI-search subjects. Its strongest pieces take a position on issues such as which AI metrics matter to boards. The team refers to tests, but it does not publish the underlying results as research.

Impression appears in the tracked AI answers more often than almost all other agencies. It sits near the top of the field for its own AI visibility.

Impression has a large team and a strong external reputation, including B Corp certification and several agency-of-the-year wins. No published job title across the team specifically carries AI search.

Impression publishes no clear price for its AI service. You will need to ask what the service costs and what the proposed work includes before making a meaningful comparison.

Reboot publishes AI-search work with measurable results and explains the approach used. The evidence is stronger where the agency describes its method than where it identifies the underlying measurement source.

Reboot explains how it tracks and monitors AI visibility. It also publishes dedicated material about AI visibility measurement and audits. That gives buyers a clearer sense of the work, although the published evidence does not cover every reporting detail.

Reboot has the lowest review score in the study, based on a relatively small number of reviews. Around a third are rated one star. Two readable reviews mention search work, so anyone considering Reboot should read the negative feedback carefully.

Reboot published a controlled GEO experiment that states its hypothesis and method, gives the results in full and explains where the experiment failed. The study planted a fact that existed nowhere else, then tested whether AI models would repeat it. That makes the work unusually easy to examine, even if the test itself was deliberately artificial.

Reboot appears in the tracked AI answers occasionally. Its visibility sits slightly below the middle of the field.

Reboot has a dedicated AI-search job title, clearly identified leadership and more than a decade of company history. Agency recognition and conference speaking add external evidence.

Reboot publishes one figure for the service that performs the AI work and explains the reason for the entry point. It publishes no tiers, minimum term or notice period. Ask how the scope and price change as the engagement grows.

Propellernet publishes two pieces of client work that name AI visibility. Both name the clients and state year-on-year periods. One explains the method properly, but neither provides a before-and-after pair or names the source of the figures.

Propellernet takes one of the clearest positions on measurement in the study. It explains which metrics the agency trusts and which it does not. The published approach includes two named instruments, a defined competitor set and quarterly reporting. Reporting stops at visibility, so ask how the agency would connect the work to enquiries or revenue.

Propellernet has a perfect average from a small number of reviews, but little written detail. The one substantive review is nine years old and does not describe the work. That leaves limited recent evidence for a buyer to assess.

Propellernet publishes a quarterly AI-adoption tracker with a national polling firm, based on representative samples. The research is published in full and provides a stronger evidence base than most agency content in the study.

Propellernet appears in the tracked AI answers with a middling level of visibility. It sits around the middle of the field on this measure.

Propellernet is the first agency here to reach the top band for staffing. Three job titles carry the discipline outright, with more carrying it in their headlines. The agency is B Corp certified, has two agency-of-the-year wins this year and has more than two decades on its company record.

Propellernet publishes one figure, which covers training. It does not explain what changes the price of an engagement, and no minimum term appears. Ask for the cost and scope of the wider service before comparing it with other agencies.

Passion Digital publishes one AI-search case study. It includes a before-and-after pair for visibility share and explains the five-step method. The client is unnamed, and the figures have no stated source, so the results are difficult to verify.

Passion Digital has an AI-search service with its own sub-pages. It names what gets measured across four engines, names two instruments including one of its own, builds prompts per client and reports through to traffic and leads. It does not state how often it samples the results.

Passion Digital has a strong average across a good number of reviews, all around a year old. One names search work. The others are general, and one comes from a partner agency.

Passion Digital covers seven distinct AI-search subjects. Its strongest piece explains how to identify AI crawlers that ordinary analytics miss. The wider material relies on other people's figures and contains no analysis of the agency's own dataset.

Not rated. Passion Digital joined the prompt set we track too recently to have a reading. This criterion therefore drops out of its average and counts neither way.

The team page and LinkedIn agree, and neither shows a job title aligned to AI search. Award recognition and recent finalist places provide external evidence, while the company record is clean.

Passion Digital publishes no price for any service. The enquiry form includes a budget selector, which shows the bands the agency works in. It does not explain what any band buys.

Polaris Agency has one AI-search case study, and it is among the best evidenced in the study. It names the client, includes a quote from that client, gives the starting position in figures, states the period and shows a substantial change. It does not identify the instrument that produced the figures.

Polaris Agency publishes a full GEO service tree. Its tracking page names what gets measured, and reporting reaches referral attribution and conversion. The agency takes a deliberate position on instruments, building the stack around each client without naming a platform. It sets no reporting rhythm.

Polaris Agency has a decent average across a modest number of reviews. One names search work, one covers email marketing and one offers general praise. The newest review is a year old.

Polaris Agency covers more than six distinct AI-search subjects, and its playbooks take positions of their own. Where figures appear, the agency cites other sources. It publishes no analysis of an original dataset about generative search.

Polaris Agency appears in AI answers to our tracked prompts a fair amount. It sits in the upper half of the field for its own AI visibility.

Polaris Agency has a small team with no AI-search job title. The search director named on LinkedIn is the same person quoted in the AI case study, which supports both claims. The agency also has a strong and recent run of search award wins.

Polaris Agency has a dedicated pricing page with three tiers, figures and the team provided at each level. That is unusual and useful. The tiers cover search, content and digital PR, while the GEO pages carry no figure of their own.

Found publishes one case study that names AI visibility. Its figure shows the share of citations attributed to content, so it measures attribution rather than a change in visibility. The case study gives no starting point, period or instrument, and reuses the same figure as proof on several service pages.

Found publishes a full service tree covering individual answer engines. It names what gets measured across five platforms, uses its own named product as the instrument, tracks continuously and builds prompt work for each client. Reporting stops at visibility and sentiment.

Found has a strong average from a small number of reviews. One names search work, while the others cover web projects and general praise. The newest review is two years old.

Found covers ten or more distinct AI-search subjects. Its best pieces take positions of their own. The agency publishes no analysis of an original dataset.

Found appears in AI answers to our tracked prompts more often than any other agency in the study.

Found publishes a large team, corroborated on LinkedIn. Neither source shows an AI-search role. The only AI wording appears in a director's positioning headline. Award shortlists and wins provide external evidence.

Found publishes three price bands with figures and explains what changes the price. It does not itemise what each band includes, and the AI-search pages carry no figure of their own. Ask for a scope and price specific to the AI-search work.