Entity Optimization
Ensure AI systems clearly understand who you are, what you offer, and how your brand relates to the broader concepts in your industry.
Generative Engine Optimisation helps your business improve visibility in AI-powered search experiences such as Google AI Overviews and ChatGPT Search. This service makes it easier for AI systems to understand, reference, and surface your content, while reinforcing the SEO foundations that still matter for long-term search performance.
Large Language Models (LLMs) and AI search engines read the web differently than traditional crawlers. They look for direct answers, unique information gain, and strong entity associations. If you aren't optimizing for extraction, you won't be cited.
Ensure AI systems clearly understand who you are, what you offer, and how your brand relates to the broader concepts in your industry.
Format your content specifically for AI extraction. Use conversational framing, clear lists, and structured data that LLMs easily digest.
LLMs ignore repetitive content. We focus on injecting unique perspectives, proprietary data, and expert insights that AI cannot find elsewhere.
Generative bots like ChatGPT-User and Google-Extended still need to fetch your site. We ensure your technical foundation allows seamless crawling.
AI learns from the broader web. We help position your brand alongside established industry entities in places where LLMs are actively trained.
Build the Experience, Expertise, Authoritativeness, and Trustworthiness signals that safety filters in generative models require before referencing you.
You receive actionable strategies that bridge the gap between traditional SEO ranking and the new world of generative engine citations and brand visibility.
An analysis of how your brand and target keywords are currently handled by Google AI Overviews, Perplexity, and ChatGPT.
A mapping of your digital brand footprint, identifying gaps in how LLMs perceive your authority and industry relevance.
Custom templates and rules for your content team on how to structure headings, lists, and answers to maximize LLM extraction.
A prioritized list of updates for existing pages, technical tweaks, and external PR targets designed to boost your citation likelihood.
Ranking #1 in traditional search isn't enough if an AI summary pushes your link down the page and fails to cite your brand in the answer.
The methodology relies on understanding natural language processing (NLP), semantic search relationships, and how LLMs are trained to summarize web content.
We analyze how AI models currently "view" your business. We map out the relationships between your brand, your products, and core industry concepts to establish a baseline for your digital entity.
We revise your most valuable pages. This involves adding clear definitions, structuring data into easily digestible formats (like tables and lists), and injecting unique information that generic AI answers lack.
Because LLMs learn from trusted sources, we develop a strategy to get your brand mentioned alongside established entities, publications, and databases that feed these AI training models.
Understanding the shift from traditional search optimization to generative engine strategies.
SEO (Search Engine Optimization) focuses on ranking links on a search results page by matching keywords and building links. GEO (Generative Engine Optimization) focuses on having your brand, data, and content cited directly within AI-generated summaries and conversational answers.
No. GEO builds upon a strong SEO foundation. AI engines like Google's AI Overviews still rely heavily on traditional ranking signals (like technical health, crawlability, and domain authority) to determine which sources are trustworthy enough to cite in their generated answers.
We target the major platforms shaping the future of discovery: Google AI Overviews (SGE), OpenAI's ChatGPT Search, Perplexity AI, and Microsoft Copilot (Bing Chat).
GEO content heavily prioritizes "Information Gain" (unique insights not found elsewhere), utilizes highly structured formatting (clear QA formats, tables, semantic HTML), and is written to be easily parsed and extracted by natural language processing models, rather than just keyword stuffed.
This depends on the specific engine. Search-grounded AI (like Google AIO or ChatGPT Search) can update citations as soon as your page is re-crawled (days to weeks). Foundational model knowledge (what the LLM "knows" without searching) only updates when the model undergoes new training runs (months).
Absolutely. If the bots that feed these AI engines (like GPTBot or Google-Extended) cannot crawl, render, or understand your website due to technical errors, your content will never make it into the AI's answer, regardless of how well it's written.
Let's optimize your digital presence for the next generation of search engines and ensure your brand is the one being cited.