AI search is already happening
Buyers are asking ChatGPT, Perplexity, and Gemini which vendors to consider before they ever run a Google search. If your brand isn't in those answers, you're not in that consideration set.
GSO / GEO / AIO Services
LLM & Generative Search Optimisation — be found in AI, not just Google
ChatGPT, Perplexity, Gemini, and Claude now answer millions of commercial searches every day. We help enterprise technology brands get retrieved, referenced, and trusted by these systems.
The Visibility Gap No One Is Measuring
Traditional SEO doesn't transfer
A page optimised purely for keywords and backlinks may never appear in an AI-generated response, no matter how well it ranks. LLMs retrieve based on semantic clarity and entity trust — not PageRank.
This is costing pipeline now
For enterprise technology brands in competitive categories — cloud infrastructure, cybersecurity, open source, AI platforms — competitor displacement in AI responses is already happening. We measure it from day one.
SEO vs GSO
How LLM Optimisation Differs From Traditional SEO
GSO isn't a replacement for SEO — it's the layer above it. Both disciplines matter, and they reinforce each other when aligned correctly.
| Category | Traditional SEO | LLM Optimisation (GSO) |
|---|---|---|
| Target systems | Google, Bing SERPs | ChatGPT, Perplexity, Gemini, Claude, AI Overviews |
| Primary signal | Backlinks, keyword relevance | Semantic structure, entity trust, citation patterns |
| Content goal | Rank for queries | Be retrieved and cited in AI-generated responses |
| Key techniques | Meta tags, link building, canonicalisation | Schema markup, structured data, entity alignment |
| Measurement | Clicks, impressions, rankings | LLM visibility scores, citation frequency, prompt coverage |
| Output | Blue link in SERP | Brand mention in AI-generated answer |
What Our LLM Optimisation Service Covers
Generative Visibility Audit
Before we build anything, we establish a clear baseline — mapping exactly how each model currently treats your brand and your category.
- Full audit across ChatGPT, Gemini, Perplexity, and Claude
- Competitor displacement analysis — who's being cited instead of you, and why
- Content and knowledge gap identification
- Prioritised fix list ranked by retrieval impact
Entity & Source Alignment
LLMs form trust judgements based on how consistently your brand is defined across the web. Ambiguous signals lead to misattribution and under-citation.
- Entity alignment across Wikidata, Crunchbase, LinkedIn, and industry directories
- Disambiguation — AI cites your company, not a similarly named one
- Consistent author, product, and service definitions across all properties
- PR and content placement in LLM-weighted sources
Semantic & Structural Optimisation
An actionable plan is then generated from these LLM insights, which is fed into advanced AI models (such as Gemini, GPT, Sonar, and Claude) for deep research. This helps identify real search queries occurring within each LLM related to your core topics.
RAG & AI Bot Accessibility
Real-time AI tools use Retrieval-Augmented Generation to pull live content into responses. Technical barriers mean you won't appear regardless of content quality.
- AI bot accessibility audit across all key pages
- Parsability issue resolution — structural blockers removed
- robots.txt and meta directive conflicts resolved
- Content delivery and rendering issues for real-time retrieval
How an Engagement Works
We operate as the intelligence layer across your marketing function — integrating with your existing PR, content, and paid teams.
Weeks 1–2 - Audit & Baseline
Full generative visibility audit. Competitor displacement mapping. Content gap analysis. Baseline LLM visibility scores established.
Week 3 - Strategy & Prioritisation
Prioritised GSO roadmap delivered. Quick wins identified. Longer-term content strategy framed around LLM prompt patterns.
Ongoing - Implementation
Structured data deployment. Content briefs developed and executed. Entity alignment work. Citation placement in LLM-weighted sources.
Monthly - Measurement & Iteration
LLM visibility tracking across target topics. GSC and AI Overview impression data. Competitor monitoring. Strategy adjusted on model shifts.
Frequently Asked Questions
What is LLM optimisation?
LLM optimisation (also called Generative Search Optimisation or GSO) is the practice of structuring your content and digital presence so that large language models — ChatGPT, Gemini, Perplexity, Claude, and others — retrieve, reference, and cite your brand accurately in their responses. It's distinct from traditional SEO, which focuses on ranking in Google's SERP. LLM optimisation focuses on appearing in AI-generated answers.
How is LLM optimisation different from SEO?
Traditional SEO optimises for search engine crawlers and ranking algorithms — backlinks, keyword relevance, meta tags. LLM optimisation targets the retrieval and reasoning processes of language models — semantic clarity, entity trust, structured data, and citation patterns. The two disciplines are complementary, not competing. A strong LLM optimisation strategy builds on a solid SEO foundation.
Which AI platforms do you optimise for?
We optimise for all major AI search surfaces: ChatGPT (including GPT-4o's web browsing), Perplexity, Google Gemini, Claude, Microsoft Copilot, and Google's AI Overviews in Search. Each platform has different retrieval behaviours — we audit and optimise for each individually.
How do you measure LLM visibility?
We use a combination of proprietary tooling and third-party LLM visibility platforms to track how your brand and key topics appear across AI systems. Metrics include citation frequency, prompt coverage (how many relevant queries surface your brand), competitive displacement rate, and sentiment accuracy. We also monitor Google Search Console for AI Overview impressions alongside traditional ranking data.
How long does it take to see results?
Structural fixes — schema, entity alignment, accessibility — can produce measurable changes in AI visibility within 4–8 weeks. Content-driven improvements typically show impact over a 3–6 month horizon, in line with how LLMs update their knowledge and retrieval patterns. We establish a baseline in the first two weeks so progress is always measured against real data.
Ready to Close the AI Visibility Gap?
If your brand isn't appearing in AI-generated answers for your category, your competitors probably are. We'll show you exactly where you stand — and what it takes to change it.
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