LLMO & Entity Optimization — EMEA
Get cited. Not just ranked.
AI search doesn't hand back ten blue links — it hands back one answer. I help EMEA brands become the entity that ChatGPT, Perplexity, and Google AI Overviews choose to cite, through entity optimization, schema and knowledge-graph work, and multilingual content architecture.
Author of the AI Discovery Playbook 2026 — a 53-page LLMO framework covering AI Overviews, ChatGPT Search, Perplexity, entity optimization, and a 90-day roadmap for EMEA brands.
Why this matters now
The answer engine has already replaced the results page
Search hasn't disappeared — it's been re-routed through models that read, summarize, and cite before a user ever sees a list of links. If your brand isn't structured for machines to understand and quote, you're invisible at the exact moment the answer is being written.
25%
Projected decline in traditional search engine volume by 2026, as users shift to AI chatbots and virtual agents.
Source: Gartner →2B+
Monthly users now see an AI-generated overview instead of a traditional Google results page.
Source: Semrush →~3.4x
Growth in Perplexity's monthly query volume between mid-2024 and mid-2025 alone — a fraction of Google's scale, but the fastest-growing entry point for research and purchase decisions.
Source: index.dev →Method
A three-step LLMO framework, built for multilingual markets
Most AI-visibility advice is written for one language and one market. EMEA is neither — this framework is built to hold up across diacritics, dialects, and platforms.
Find out where you actually stand
Baseline your current AI citation rate across ChatGPT, Perplexity, Google AI Overviews and AI Mode. Audit existing schema, entity coverage, and knowledge-graph presence. Map where competitors are getting cited instead of you, and why.
Make your brand machine-readable
Implement JSON-LD and schema markup across priority pages. Strengthen entity associations so knowledge graphs and LLMs resolve who you are without ambiguity. Restructure content into citation-ready passages — facts and semantic triples, not narrative padding.
Hold visibility as markets and models shift
Extend the same entity and schema foundation across your EMEA-language markets — diacritic and non-diacritic variants, local intent, and platform-specific quirks. Monitor citations monthly and recalibrate as AI platforms update their retrieval behavior.
Packages
Three ways to work together
Each engagement builds on the last — start with a diagnostic, move into structural work, then hold visibility over time. Best fit depends on where you are today.
No fixed price list, by design. Scope and investment depend on how many markets, languages, and platforms are in play — every engagement is sized on the discovery call, not before it.
AI Visibility Audit
Best fit: brands who need a clear diagnostic before committing budget.
Typical duration — 2 weeks- Full entity & schema audit of priority pages
- AI citation baseline across ChatGPT, Perplexity, Google AI Overviews & AI Mode
- Competitor citation gap analysis
- Prioritized 90-day roadmap
Entity & Knowledge Graph Build
Best fit: brands ready to implement structural fixes across one or more markets.
Typical duration — 6–8 weeks- Full JSON-LD / schema markup rollout
- Knowledge-graph entity optimization and disambiguation
- Content restructured into citation-ready, machine-readable passages
- Multilingual entity mapping for target EMEA markets
LLMO Growth Partnership
Best fit: brands and agencies managing AI visibility across markets, on an ongoing basis.
Ongoing — monthly engagement- Continuous AI citation monitoring across major platforms
- Monthly schema and content iteration
- Quarterly strategy recalibration with stakeholder reporting
- Multilingual rollout support as new markets open
Credentials
Built from practice, not theory
AI Discovery Playbook 2026
A 53-page LLMO framework written for the EMEA market — covering AI Overviews, ChatGPT Search, and Perplexity behavior, entity optimization, schema and structured data, AI visibility measurement, multilingual strategy, a 90-day roadmap, and the 2026 toolstack. Built to help in-house teams operationalize LLMO, not just understand it.
Active across four markets
Currently running LLMO and SEO strategy work spanning English, Arabic, Hebrew, and Serbian-language search and AI environments — direct exposure to how citation behavior differs by language and platform, not a single-market playbook applied everywhere.
Core capabilities
FAQ
Before you book the call
LLMO — large language model optimization — is about structuring a brand's entity, content, and data so AI systems can understand, trust, and cite it directly in a generated answer. Traditional SEO optimizes for ranking a page in a results list; LLMO optimizes for being the fact a model repeats, with schema, knowledge-graph signals, and content structure doing the work that backlinks and keyword density used to do.
The baseline covers ChatGPT Search, Perplexity, Google AI Overviews and AI Mode, and Gemini — the platforms with the most measurable query volume today. Copilot and other assistants get monitored as part of ongoing work, since most rely on overlapping retrieval and indexing infrastructure.
Schema and entity fixes are usually crawlable and reflected in citation checks within 2–6 weeks, since most AI platforms refresh their indexes faster than classic Google rankings ever did. Durable, competitive visibility — where you're consistently cited over rivals — is a 3–6 month build, especially across multiple languages or markets.
Both. Brands typically engage directly for the Audit or Growth Partnership. Agencies bring me in as embedded LLMO expertise on client accounts — usually white-labeled — when they need entity and schema depth their team doesn't have in-house yet.
Yes — this is the core of the practice. That means diacritic and non-diacritic keyword variants, script differences (Latin, Cyrillic, Arabic, Hebrew), and locale-specific entity disambiguation, not a single English-language framework copy-pasted across markets.
A direct look at your current AI visibility — how you currently show up (or don't) in ChatGPT, Perplexity, and Google AI Overviews for the questions that matter to your business — followed by an honest read on what's realistic to fix first and what scope and timeline that would take. No deck, no generic pitch.
There's no published price list, on purpose — the right scope depends heavily on how many markets, languages, and platforms are in play. Investment is set after the discovery call, once the actual gap and goal are clear.
Most engagements work alongside an existing team rather than replacing one. The Audit and Build packages are typically handed off with clear documentation your team can implement or maintain; the Growth Partnership sits as the specialist layer on top of your day-to-day SEO and content work.
Start here
Let's find out where you stand in AI search.
One call. No deck, no pitch — just a direct look at your current AI visibility and what's realistic to fix first.
Book a Discovery Call