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Get found and cited in AI answers — not just ranked in Google

Buyers increasingly ask ChatGPT, Claude, Perplexity and Google AI Overviews before they ever open a search results page. Generative Engine Optimization (GEO / AEO) makes your brand unambiguous to those models, your content extractable and citable, and your presence real across the sources they draw from — measured honestly, with no guarantees nobody can keep.

Scope of this page

Where GEO sits — next to SEO, not instead of it

GEO does not replace search engine optimization. SEO gets you found and ranked by search engines; GEO gets you found, understood and cited inside AI answers. If your current work stops at the search results page, this is the layer above it.

  • Shares a foundation with SEO

    Structured data and clean, crawlable output are common ground — everything above them diverges. SEO ranks you; GEO gets you cited.

  • Distinct from agent-ready architecture

    GEO is about the visibility of your brand and content in AI answers. Agent-ready architecture is about making your product operable by agents. Different buyers, often run together.

Find you / cite you / use you — search engines find you (SEO), LLMs cite you (GEO), agents use you (agent-ready). One triad, three disciplines, no overlap.

01  ·  Operating model

How we approach GEO — earned, not gamed

A delivery model built on entity clarity and real presence, not tricks that stop working the moment a model updates.

  • 01Entity before content — we make who you are unambiguous, with a consistent name, place and identity across the web, before producing anything.
  • 02Earn citations, don't game them — models cite sources they can trust and extract. That comes from structure and presence, not keyword stuffing for robots.
  • 03Be present where models look — AI answers are drawn from real sources: directories, profiles, authoritative pages. We build legitimate presence there, region by region. No spam, no manipulation.
  • 04Measure what's observable, name what isn't — there is no ranking dial inside an LLM. We track what can be tracked and tell you plainly where the limits are.
  • 05Engine- and region-neutral — ChatGPT, Claude, Perplexity and Gemini / AI Overviews each weight sources differently, and a DACH answer differs from an APAC one. We optimise for coherence across all of them, not one engine.
02  ·  What we build

What we build

01

Entity foundation

An unambiguous brand entity models can resolve and trust. · Consistent NAP across every surface · Organization / Service schema (JSON-LD) · sameAs graph linking your real profiles · Knowledge-graph and Wikidata signals where relevant · One coherent identity, not five conflicting ones

02

Citation-ready content

Content structured so a model can extract and cite it cleanly. · Clear, self-contained claims and definitions · Question-led sections (AEO) that answer directly · Comparison and decision content models reach for · Sourced, factual statements over marketing fog · Structure that survives extraction out of context

03

Off-site presence & entity building

Legitimate presence in the sources AI answers draw from. · Region-specific authoritative directories and profiles · Review and reputation platforms relevant to your market · Consistent entity data across every listing · No link spam, no manufactured presence — UWG-aware

04

Technical legibility

The shared foundation that makes everything else readable. · Structured data across key pages · llms.txt and machine-readable site context · Clean SSR / crawlable output · Coordinated with your SEO and agent-ready layers

05

Answer engine optimization (AEO)

Targeting featured answers and AI Overviews directly. · Question → concise extractable answer patterns · FAQ schema on high-intent pages · Definition and "what is" assets · Structure aligned to how answer engines quote

06

Measurement & monitoring

Honest visibility into what's actually working. · Citation and mention tracking across engines where observable · Prompt-based testing — asking the models directly, recording how you appear · AI-referral traffic where attributable · Entity-consistency monitoring over time

03  ·  How we work

How we work

  1. Step 01

    Entity & citation audit

    We test how your brand currently appears across AI engines, check entity consistency (NAP, schema, sameAs), and find where you're invisible, misrepresented or inconsistent.

  2. Step 02

    Entity foundation

    We fix the structured data, NAP, sameAs graph and knowledge-graph signals so models resolve you to one coherent entity.

  3. Step 03

    Citation-ready content & structure

    We produce or restructure content so models can extract and cite it — question-led, self-contained, factual.

  4. Step 04

    Off-site presence

    We build legitimate presence in the directories, profiles and platforms your markets' AI answers actually draw from — region by region.

  1. 05
    Monitoring & iteration

    We track observable citations, mentions and referrals, re-test against the engines, and iterate on what moves.

04  ·  Outcomes

Outcomes we optimise for

Real visibility in AI answers — not vanity metrics.

05  ·  When it fits

When GEO / AEO makes sense

Choose this service when:

  • Your buyers research through ChatGPT, Claude, Perplexity or AI Overviews before they reach Google
  • Your category — B2B, SaaS, professional services — is increasingly answered by AI, not links
  • Your brand is invisible, outdated or misrepresented when you ask the models directly
  • You operate across multiple markets or languages and need one coherent entity per region
  • You already invest in SEO, but it stops at the search results page
  • You want demand from AI discovery without buying into guarantees nobody can keep
06  ·  Problem

Why most GEO work is snake oil

The GEO market is full of promises nobody can keep.
Measurement · what's actually trackable

Honest dashboards over vanity metrics

GEO measurement is partial by nature, and we'd rather say so than invent certainty. Here is what we can actually track.

  • Brand mentions and citations across engines, where tools and APIs expose them
  • Prompt-based testing — asking the models directly and recording how, and whether, you appear
  • AI-referral traffic, where it's attributable in analytics
  • Entity-consistency signals across your listings and structured data

What we don't promise: a "rank" or guaranteed citation share inside any model — those don't exist; that a specific prompt will always return your brand — model outputs vary. We report what's observable and changing, name what isn't, and never dress probability up as a guarantee.

Multiple engines, multiple markets

One coherent entity across every answer

Different engines and markets pull from different sources. ChatGPT, Claude, Perplexity and Gemini / AI Overviews weight sources differently; a DACH buyer's AI answer and an APAC buyer's draw from different regional sources and languages.

  • Entity consistency across every engine and listing — one identity, not five
  • hreflang-aligned structured content so each region resolves to the right you
  • Region-appropriate source presence — the directories and profiles that market's answers draw from
  • The same legal and locale discipline that governs your site, applied to every off-site profile and structured claim

Strong in one engine and absent in the next is the failure mode we design against — coherence across all of them, instead of gaming one.

Reference stack

Default choices — with opt-in pieces where the market needs them

Default choices
  • Organization / Service / FAQ schema (JSON-LD)
  • llms.txt
  • Consistent NAP & sameAs entity graph
  • Question-led, extractable content structure
  • Clean crawlable SSR output
Added where needed
  • Region-specific off-site profile & directory build
  • Citation / mention monitoring across engines
  • Prompt-testing harness
  • Knowledge-panel / Wikidata entity work
  • Comparison, definition and decision content assets

Engine- and region-neutral. The entity and structure work is the default; monitoring, off-site builds and entity-graph work are added where the market and budget justify them — never manipulation, never link spam.

FAQ

FAQ

  1. Generative Engine Optimization (and answer engine optimization) is the work of making your brand and content visible, correctly represented and citable inside AI answers — ChatGPT, Claude, Perplexity, AI Overviews — rather than only in search results.

  2. No. SEO gets you ranked by search engines; GEO gets you cited by AI answers. They share a technical foundation but diverge above it. Most teams need both.

  3. No — and anyone who guarantees it is selling something that doesn't exist. There's no ranking dial inside a model. We make you the kind of source models cite, and we measure what's observable.

  4. GEO is about the visibility of your brand and content in AI answers. Agent-ready architecture is about making your product operable by agents. Different goals, often run together.

  5. Citation and mention tracking where engines expose it, prompt-based testing against the models, attributable AI-referral traffic, and entity-consistency signals. Honest dashboards, not invented metrics.

  6. Yes. AI answers and search engines both still send buyers, and GEO builds on solid SEO foundations rather than replacing them.

  7. Each engine weights sources differently. We optimise for coherence across all of them rather than gaming one, so you stay consistent as engines and their sourcing change.

  8. Entity and structure fixes register as engines re-crawl and re-index. Citation visibility builds over months as presence and content compound — it's closer to SEO's timeline than paid media's.

  9. Yes. We run it for our own studio in four languages across three regions, with consistent entity data and locale-appropriate source presence per market.

Adjacent plates

Related services

  1. 01SEO Migration & RelaunchProtect search value when the site changes — and keep GEO signals intact too.Open
  2. 02Lead Generation WebsitesSEO- and AI-search-ready sites connected to CRM and analytics.Open
  3. 03Agent-Ready ArchitectureMake the product itself operable by AI agents.Open
  4. 04Frontend DevelopmentCrawlable, structured output GEO depends on.Open
  5. 05Data Engineering & AnalyticsThe measurement layer behind honest GEO reporting.Open
How do you appear right now?

Curious how you appear in AI answers right now?

An entity & citation audit tests your brand across the major AI engines, checks your entity consistency, and shows exactly where you're invisible, inconsistent or misrepresented — before any work starts.

Book an entity & citation audit
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H-Studio runs Generative Engine Optimization (GEO / AEO) for B2B and SaaS brands across DACH, Russia and APAC — entity foundations, structured data, llms.txt, citation-ready content and legitimate off-site presence in the sources AI answers draw from. We make brands visible and correctly cited in ChatGPT, Claude, Perplexity and AI Overviews, measured honestly, with no guarantees nobody can keep — the same work we run on our own three-region studio.