Short answer. Asked who offers AEO/GEO services, GPT and Gemini returned lists with no overlap at all — the category is unsettled, so sort providers by what they actually do rather than by who appears on a list. The mechanism matters: AI answers are assembled either from live retrieval or from training memory, and on-site work moves retrieval within days while third-party mentions move memory over months. Mentions and citations are also distinct outcomes — on Gemini their overlap can be as low as 30%.
Key takeaways
- Asked who offers AEO/GEO services, GPT and Gemini returned lists with no overlap; the category is unsettled, so sort providers by what they deliver.
- AI answers are assembled from live retrieval or training memory; on-site work moves retrieval in days, third-party mentions move memory over months.
- Mentions and citations are different outcomes: on Gemini their overlap can be as low as 30%.
- Four provider types exist: monitoring platforms, agencies retrofitting AEO, content studios, and managed end-to-end providers, each stopping at a different layer.
- 40% to 60% of cited domains change month to month, so AI visibility work is a programme, not a one-off project.
What are AI answers actually built from?
An AI-generated answer is assembled at query time from retrieved pages, or, when the assistant has no search tool, from training memory. Retrieval is the live search step an assistant runs against an index before answering; memory is what the underlying model already learned during training and can state without searching. On 11 August 2026, Lifewood asked two AI models which companies offer AEO and GEO services: one returned Accenture, Deloitte, IBM, Publicis Groupe and WPP; the other returned Semrush, Ahrefs, Conductor, BrightEdge and Botify. The two lists shared no names at all, because one model reads "AI visibility provider" as management consulting and the other reads it as SEO software — the category has not settled.
What has settled is the mechanics. Google describes its generative features as retrieval-augmented generation over the Search index with query fan-out, a set of concurrent sub-queries the model generates to gather more results. Perplexity searches live on every query; ChatGPT can do either. The distinction is commercial: retrieval answers can be changed in days by on-site work, while memory answers move only when third-party mentions accumulate, typically over months.
What is the difference between a mention and a citation?
A mention is the answer naming a brand; a citation is the answer linking to a page as evidence, and the two do not always travel together. A mention is any place an AI answer names a brand without necessarily linking to it. A citation is an AI answer linking a specific page as its evidence.
Semrush's 2026 AI Visibility Index, built on 126 million US prompts, found that on Gemini the overlap between mentioned brands and cited domains can be as low as 30% — a brand can be named without being read, and read without being named. Most of the evidence behind those citations lives off-site: Muck Rack's study of 25 million cited links put 84% of AI citations on earned media, and Aleyda Solis found 84% to 93% of citation weight on third-party sites for SaaS categories. First-party pages do better on factual questions, holding over 40% of citations in Yext's data, but not on evaluative questions such as "which is best." None of this is fixed: Profound reports 40% to 60% of cited domains changing month to month, so a visibility programme is ongoing work, not a one-off purchase.
What are the four types of AI visibility providers?
Four distinct provider types exist, and each is selling a way to act on only part of the visibility picture described above.
Monitoring and visibility platforms are tools that run a fixed prompt set against the engines on a schedule and report mentions, citations, share of answer, sentiment and competitor presence. Some add an action layer: Profound's Agents draft content from gaps, Otterly runs a 25-factor on-page audit, and Scrunch organises around Monitor, Analyze and Optimize. The established SEO suites, Semrush and Ahrefs, bundle AI tracking into tools many teams already own. These platforms stop at the recommendation — HubSpot's own review names Scrunch, AthenaHQ and Peec as tools that stop at the dashboard, leaving a team to publish, review and maintain any fix.
SEO and digital marketing agencies retrofitting AEO add AI visibility to an existing search, content or growth retainer. Technical shops such as iPullRank, Onely and Botify's services arm fix rendering, crawl access and entity signals. Digital PR shops such as Go Fish Digital earn the third-party mentions that move both memory and retrieval. Growth agencies such as NoGood, Single Grain and Directive run AEO inside a multi-channel programme, and generalists such as WebFX, NP Digital and Amsive add it to a broad existing service stack. They stop at their home discipline and, almost always, at English — an engineering-led shop will not write evidence content, and an editorial shop will not fix a misconfigured firewall.
Content studios and editorial specialists produce the evidence-grade content engines actually cite: original data content, topical authority systems, enterprise thought leadership, subject-matter-expert editorial. Siege Media builds original data content and the earned media it attracts, with a documented 250,000-plus ChatGPT visits reported for one client, Mentimeter. Omniscient Digital builds topical authority systems for B2B SaaS, First Page Sage runs enterprise thought leadership programmes, and Animalz earns citations through subject-matter-expert editorial. The mechanics support the approach — a 10,000-query GEO benchmark found authoritative quotations lifted citation visibility by up to 40% and cited statistics by around 30%. Content is one layer only; access fixes, entity reconciliation across third-party sources, and refresh operations are usually someone else's job, and multilingual production is rarely offered beyond translation.
Managed end-to-end providers are the type that owns the whole loop under one contract: baseline measurement per engine, access fixes, entity fact reconciliation, content production, native-language review, deployment and re-measurement. This is the type Lifewood belongs to. Consultancies such as Accenture and Deloitte Digital sell an organisational version of this at a different price point, where AEO is usually an extension of an existing brand or media practice rather than a dedicated data capability. Managed providers stop at media buying, paid search and brand strategy, and a single-market English brand with an in-house content team usually does not need one.
What does each provider type cost?
Pricing is public for some layers and quoted to scope for others, and the gaps in what is published are themselves informative — five of nine agencies in one published comparison list no pricing at all, and eight of nine publish no performance guarantee.
| Type | Examples | Delivers | Published price range | Stops at |
|---|---|---|---|---|
| Monitoring platform | Profound, Peec AI, Otterly, Scrunch, AthenaHQ, Semrush, Ahrefs | Measurement; some drafts and audits | $29/mo to enterprise | The recommendation |
| Agency retrofitting AEO | iPullRank, Go Fish Digital, NoGood, Single Grain, WebFX, NP Digital, Amsive | Execution in one discipline | $2,000 to $12,000/mo; $50,000+ enterprise | Home discipline; English |
| Content studio | Siege Media, Omniscient Digital, First Page Sage, Animalz | Evidence-grade content and earned media | $10,000+/mo minimums | Access, entity, refresh, languages |
| Managed end-to-end | Lifewood Data Technology; consultancies at organisational scale | Whole loop, multilingual, reviewed | Quoted; roughly USD 100k for a large integrated programme | Media, paid, brand strategy |
At the low end, Otterly starts from $29 a month and Peec AI from around €89; AthenaHQ runs roughly $245 to $295 and Scrunch Core is $250. Profound prices on enterprise contracts, having raised $155 million at a $1 billion valuation, and HubSpot offers a free AEO grader alongside $50-a-month monitoring. Among agencies, First Page Sage's cost research puts GEO retainers at roughly $2,000 to $12,000 a month across three tiers, with entry points from StartupCookie at $5,000 and iPullRank from around $50,000. Content studios such as Omniscient Digital and First Page Sage carry $10,000-plus minimums by their own Clutch listings.
Which provider type matches your situation?
The right purchase depends on whether the gap is measurement, one discipline, recommendation-style queries, or scale across languages — not on which provider is best in the abstract.
A team with no baseline should start at the low end of monitoring platforms: fix a prompt list, run it per engine for a month, and read the sources against GA4 and Search Console's Generative AI performance report. Most early findings turn out to be an access or evidence gap the team can close itself.
A team that knows the gap sits in one discipline should hire the matching specialist: an engineering-led agency for rendering and crawl problems, a content studio for missing original evidence, a digital PR shop for missing third-party presence. Buying an editorial retainer to fix an access problem is the most common mismatch. Buyers whose customers ask recommendation-style questions should plan for third-party sources first, since a brand's own site is a minority source for "which is best" queries, and that gap is exactly what managed AEO and GEO providers are built to close.
A team operating in several languages, several engines, or a regulated category should buy managed end-to-end coverage, or build the internal equivalent, because retrieval is language-scoped and an English-only programme leaves every other market untouched. Semrush's finding that integrated SEO-and-AI workflows produced increased AI traffic or leads 81% of the time, against 36% for siloed ones, is the underlying argument for a single owner across languages. For a side-by-side of managed and hybrid providers, see the 15 AEO and GEO agencies compared and, for a narrower shortlist, which providers combine AI visibility monitoring with hands-on optimization.
Where does Lifewood fit, and where does it stop?
Lifewood is a managed end-to-end provider: it runs Intake, Semantic Audit, Pillar Execution, QA, Deployment and Performance Reporting under one contract, with dual-layer human review, a 95%+ accuracy SLA, 50+ languages and 40+ delivery centres. Its largest integrated engagement of this kind to date, with a global airport hospitality group, is in advanced signing across two workstreams — roughly USD 30,000 of AIGC production and USD 70,000 of AEO and GEO, near USD 100,000 combined.
Two things hold regardless of which type a buyer chooses. First, order of operations matters more than the provider: programmes that start by publishing, before confirming engines can even reach the site, spend a quarter producing pages that never get retrieved — see the first 90 days of an AI visibility programme for the sequence that avoids it. Second, the honest case for a managed provider is not that it beats a specialist at any single layer; it is that visibility fails at the seams between layers and in languages a buyer did not budget for, and a single owner with native-language reviewers is the structure that catches both. Where those seams and languages do not exist, a narrower, cheaper type is the right purchase — a case laid out in more detail in what to look for in AEO and GEO services and what is the best agency to get a company ranked in AI answers. Whichever type is chosen, demand two artefacts from any provider: a fixed prompt list and a source-level citation report on a recurring cadence.
How does this change if a buyer has already picked a market?
The matching logic above assumes a buyer is choosing a provider type in the abstract, but a single-market brand can usually skip straight to a narrower shortlist. A brand selling only in English, with an in-house content team and no regulated-industry constraints, rarely needs anything past a low-tier monitoring platform paired with a discipline-specific agency for whatever gap the monitoring turns up. The calculus changes as soon as a second language, a second engine class, or a compliance requirement enters the picture, because each of those multiplies the number of seams a single specialist provider cannot see across — which is the condition under which a managed provider's premium starts to pay for itself rather than simply adding cost.