Generative Engine Optimization Agency (GEO)

Generative engine optimization (GEO) is the practice of optimizing your brand and content so AI search engines — Google AI Overviews, ChatGPT, Perplexity, and Gemini — cite and recommend you when buyers ask them a question. Where traditional SEO targets blue-link rankings, GEO targets the AI-generated answer itself, using structured, passage-level content, schema, and trusted brand-mention signals so the model quotes you by name.

Foundgrove's GEO services start at $2,500/month on the Growth tier, the same entry point as our SEO retainer, because GEO and SEO share most of the same foundations. Pricing scales with your market's competitiveness, content volume, and how many AI surfaces and topics you want to own. Engagements are month-to-month with no minimum and no lock-in, and there is no setup fee.

A generative engine optimization agency restructures your content for AI extraction, deploys the schema and llms.txt that let AI engines parse your site, and builds the entity and third-party-mention signals that make models trust and cite you. The GEO agencies and companies worth hiring track real AI visibility — how often ChatGPT, Perplexity, and AI Overviews actually recommend you — rather than vanity keyword rankings, and tie that back to leads.

SEO earns you traditional Google rankings. GEO (generative engine optimization) earns citations inside AI-generated results like Google AI Overviews and Perplexity. AEO (answer engine optimization) earns recommendations from chat assistants like ChatGPT and Claude. They share foundations — strong content, schema, and authority — but each needs distinct tactics. We run all three under one retainer so you show up wherever buyers search.

AI assistants recommend brands they encounter repeatedly across sources they trust, structured in a way they can extract. We build that by publishing clear, passage-level answers to the questions buyers ask, deploying schema and llms.txt for machine parsing, and earning brand mentions on the review sites, directories, and editorial sources these models weight. It is less about keywords and more about being the consistently-cited, well-structured answer.

We track AI visibility directly: how often ChatGPT, Perplexity, Gemini, and Google AI Overviews mention or recommend your brand for the prompts that matter, your share of voice versus competitors, and whether those placements cite you as a source. We pair that with the downstream signal that actually counts — leads and booked calls attributed to AI-driven discovery — in a live monthly report.

No. GEO and SEO share roughly 70% of their foundations — indexability, authority, content quality, internal linking — so an honest agency won't charge double for it. But the GEO-specific 30% is real work: passage-level rewrites so AI engines can extract your answer, schema and crawler configuration, and brand-mention building on the sources those engines cite. If a provider can't tell you which line items are genuinely new, be skeptical.

GEO (generative engine optimization) targets AI search interfaces that retrieve and cite web pages — Google AI Overviews, Perplexity, and Copilot — so it depends on passage extractability and schema. AEO (answer engine optimization) targets chat assistants like ChatGPT, Claude, and Gemini, where users delegate a decision to the model, so it leans more on brand mentions and entity signals across the open web. We run both under one retainer so you show up in each.

Faster than SEO on some dimensions, slower on others. On pages already indexed, citation presence can lift within weeks of passage rewrites — Perplexity, with its recency bias, tends to re-weight refreshed pages fastest. Citation rates usually start moving in months 3-6, and AI-referred leads become a meaningful share of total volume between months 6 and 12. Entity-signal work like digital PR compounds over 6-12 months.

No — GEO is additive, not a replacement. Roughly 70% of the work overlaps with SEO (indexability, authority, content quality, technical health), and an AI-cited page still has to be retrievable, which is a classic SEO problem. GEO adds the passage-level, schema, and mention work that earns citations on top. Dropping SEO to chase AI citations removes the retrieval foundation those citations depend on.

Publish it, but keep expectations honest. As of mid-2026 the major AI crawlers still don't fetch llms.txt in meaningful volume, so it is not a citation lever on its own. It costs about an afternoon, signals professionalism, future-proofs you if adoption grows, and helps your own internal AI tooling — so we deploy it, but we never sell it as the thing that gets you cited. Extraction-ready content does that.

The service businesses whose buyers now open ChatGPT or Perplexity before Google — high-consideration, high-lifetime-value categories like legal, dental, home services, medical, financial, and B2B services. If your customers ask AI "who's the best [service] near me" or "how do I choose a [provider]", GEO puts you inside that answer. Low-consideration, impulse purchases see less lift, because buyers rarely consult an assistant first.

No — and no honest provider can. AI engines decide their own answers, and anyone guaranteeing a citation in ChatGPT, Perplexity, or AI Overviews is promising something they don't control. What we do commit to is the work and the measurement: a documented visibility baseline, the technical and content changes that make citations possible, and monthly per-engine tracking so you can watch the trend line yourself.

Not on its own. Ahrefs' controlled study of 1,885 pages found that adding JSON-LD schema did not, by itself, lift citations on Google, ChatGPT, or Perplexity. We still deploy Organization, Article, and FAQPage schema because it earns SERP rich results and sharpens entity clarity — but we treat it as hygiene, not a citation lever. The lever is clean, extractable, well-sourced content; schema supports it rather than replacing it.

Google AI Overviews, by volume — they now appear on about 16% of US Google searches and 21% of all tracked keywords after more than doubling (+116%) since Google's March core update (Ahrefs), which still dwarfs combined Perplexity and Copilot exposure for most service businesses. Once your top commercial pages extract cleanly for AI Overviews, layering in Perplexity's recency and clean-HTML preferences is fast, and strong ChatGPT Search performance largely follows from the same work.

Yes, but less as the main lever. Links still help a page get retrieved — an engine cites what its index already trusts — while unlinked brand mentions increasingly drive whether you get named. In Ahrefs' 75,000-brand study, brand mentions correlated with AI citations roughly 3x more strongly than raw backlink count. So we build citations and mentions through genuine digital PR and treat backlinks as one output of that, not the goal: links help you get retrieved, mentions help you get attributed, and you need both.

It can make them eligible. AI answers increasingly surface images and pull from video, but only when the media is machine-readable. We write descriptive alt text, keep image metadata meaningful, deploy VideoObject schema, and publish full transcripts so the passages inside a video become extractable. No one can guarantee a specific image or clip gets cited — engines decide that — but unstructured media is invisible to a model, and structured media is at least in the running.

Often yes, if your buyers ask ChatGPT, Perplexity, or Google's AI before they choose. For a small business, GEO usually means winning a handful of high-intent prompts — "best [service] near me", "how do I choose a [provider]" — on a few commercial pages, where one cited answer can outweigh a ranking buyers never scroll to. It is a weaker fit for impulse purchases where nobody consults an assistant first. Pricing starts at $2,500/mo, month-to-month with no lock-in, so it scales to a small-business budget.

We target the prompts your buyers actually type before they buy — patterns like "best [service] near me", "how do I choose a [provider]", "is [approach] worth it", and "[option A] vs [option B]". We map each prompt to the page type best suited to win it — a service page, a buyer's guide, or a comparison — then engineer that page to extract cleanly. These are example prompt patterns, not guaranteed placements: which answers an engine cites is its call, and we track the movement monthly.