AI Online

LLM Optimisation

Get your brand cited by AI. We optimise for ChatGPT, Google AI Overviews, Perplexity and every LLM that matters.

Welcome to the SEO Strategy AI Assistant. I'm here to help with LLM Optimisation — from getting your brand cited by ChatGPT and Google AI Overviews, to schema markup, entity SEO and everything in between.

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Your own AI assistant — built for your business

The chat above is a live example. We build bespoke AI assistants like this for B2B companies — trained on your products, your documentation, your industry. Your customers ask questions in plain English and get accurate, cited answers. No hallucinations, no off-brand responses, no generic chatbot nonsense.

No hallucinations Brand-safe responses Citation enforced Analytics dashboard
Explore LLM Optimisation Topics
AI Overviews Optimisation (AIO)
Get cited in Google's AI-generated answers
Answer Engine Optimisation (AEO)
Own featured snippets, PAA & voice answers
Generative Engine Optimisation (GEO)
Get cited by AI search engines like Perplexity
AI Citations & Mentions
Monitor & improve how LLMs reference your brand
Entity SEO
Knowledge graph & E-E-A-T signals
Schema & Structured Data
Rich results & AI-readable markup
AI Persona Testing for SEO
Validate content against real buyer psychology
AI Agent Optimisation (AAO)
Be found & chosen by autonomous AI agents

What Is LLM Optimisation?

LLM Optimisation is the practice of ensuring your brand is accurately represented, frequently cited and positively positioned across large language models and AI-powered search platforms. As a dedicated generative engine optimisation agency, we deliver the full spectrum of AI visibility services: AI Overviews Optimisation (AIO), Answer Engine Optimisation (AEO), Generative Engine Optimisation (GEO) and AI Citation monitoring — combining traditional SEO fundamentals with AI-specific strategies to build visibility where an increasing proportion of business discovery now happens.

The way people find businesses has changed fundamentally. Millions of people now ask ChatGPT, Perplexity and Google AI Overviews for recommendations instead of — or before — running a traditional Google search. When someone asks an AI “What are the best managed file transfer solutions for healthcare?” or “Who are the leading SEO consultants in the UK?”, the AI generates a response that either includes your brand or doesn’t. There is no page two. There are no ten blue links to scroll through. You are either cited in the answer or you are invisible to that user entirely.

LLM Optimisation is the discipline that determines which side of that equation you sit on.

Why LLM Ranking Matters in 2026

The growth in AI-powered search is not a future prediction — it is a measurable, current reality. Search volume for “LLM optimisation” has grown 600% year-on-year. “GEO agency” is up 1,300%. ChatGPT now serves over 300 million weekly active users. Google AI Overviews appear across an expanding proportion of informational queries. Perplexity handles hundreds of millions of queries monthly. These platforms are not replacing traditional search — they are augmenting it, and for many query types, they are becoming the primary discovery channel.

LLM ranking — your brand’s position and presence in AI-generated responses — is becoming as strategically important as organic ranking has been for the past two decades. The difference is that LLM ranking is not determined by the same signals as organic ranking, although there is significant overlap. LLM ranking depends on entity authority, content structure, topical depth, source trustworthiness and the specific mechanisms each AI platform uses to retrieve and evaluate information. Understanding these mechanisms — and optimising for them systematically — is what LLM Optimisation delivers.

The commercial implications are direct. Businesses cited in AI-generated answers receive qualified referral traffic, build brand authority through AI endorsement, and capture discovery opportunities that competitors miss entirely. Businesses not cited in these responses lose visibility to competitors who are — and the gap compounds over time as AI systems increasingly favour sources they have previously cited and trust.

The Four Pillars of LLM Optimisation

LLM Optimisation is not a single tactic — it is a strategic framework built on four interconnected disciplines. Each addresses a different dimension of AI visibility, and the most effective strategies integrate all four.

Answer Engine Optimisation (AEO)

AEO is the foundational layer. It ensures your content is structured to directly answer questions across every platform that responds to queries — featured snippets, People Also Ask, voice assistants, AI Overviews and LLM search engines. AEO is about being the answer, not just a link in the results. Our AEO approach includes the proprietary Answer Intent Framework — a systematic method for categorising questions by intent type and matching each to the optimal content format and structured data. Get AEO right, and every other pillar performs better.

AI Overviews Optimisation (AIO)

AIO is Google-specific — ensuring your content is selected, cited and accurately represented in Google’s AI-generated summaries that now appear at the top of search results for many informational queries. Given Google’s continued dominance of search traffic, AIO is arguably the most immediately impactful pillar for most businesses. AIO requires strong organic rankings as a foundation (Google sources AI Overviews primarily from pages that already rank well) combined with content structure and authority signals that meet Google’s additional AI-specific evaluation criteria.

Generative Engine Optimisation (GEO)

GEO targets AI-native search platforms — Perplexity, ChatGPT with search, Microsoft Copilot and Gemini — that use retrieval-augmented generation (RAG) to produce cited, synthesised answers. These platforms retrieve web content in real-time, evaluate source authority and generate answers that cite the sources they drew from. GEO ensures your content is retrieved, evaluated as authoritative and cited in these AI-generated responses. Our GEO guide covers the RAG pipeline in detail, including how each major platform selects and evaluates sources.

AI Citation Monitoring

AI Citation monitoring provides the measurement layer that makes LLM Optimisation accountable. You cannot optimise what you cannot measure. We systematically track how your brand appears across AI platforms — which queries trigger citations, which competitors are cited instead, how citation frequency changes over time, and where the highest-value citation opportunities exist. This monitoring informs ongoing strategy and provides the data needed to demonstrate ROI from LLM Optimisation investment.

How AI Optimisation Differs from Traditional SEO

AI optimisation and traditional SEO share significant foundations — strong content, technical excellence, authority signals — but the mechanisms differ in ways that require specific strategic adaptations.

Traditional SEO targets ranking positions in a list of results. AI optimisation targets citation in synthesised answers. In traditional SEO, you compete for ten positions on page one. In AI optimisation, you compete to be one of the three to eight sources an AI synthesises its answer from — or in some cases, the single source it cites for a specific claim. The evaluation criteria overlap (domain authority, content quality, topical relevance) but AI systems add additional layers: content structure and extractability, entity recognition and trust, factual specificity and evidence quality, and freshness relative to competing sources.

The most significant difference is the role of entity authority. In traditional SEO, a strong page can rank well even if the brand behind it is relatively unknown. In AI optimisation, entity recognition is foundational — AI systems need to trust the source entity before they will cite its content. This is why entity SEO is not just a related service but the strategic foundation of our entire LLM Optimisation approach. Businesses with strong entity signals see consistently better AI citation rates than businesses producing equivalent content without entity clarity.

The Entity Foundation

Every LLM Optimisation engagement we deliver is built on an entity SEO foundation. This is not a philosophical preference — it is an observable pattern from client results. The businesses that achieve the strongest LLM ranking improvements are those with clearly defined entity signals: consistent brand naming across platforms, comprehensive structured data, verified cross-platform presence, and strong topical associations between their brand entity and their expertise areas.

Our entity-first approach means we assess and strengthen entity signals before focusing on content and platform-specific optimisation. Using our Entity Authority Maturity Model — a four-level framework for diagnosing entity health — we identify exactly where each client sits and build a roadmap from their current state to the entity authority level required for consistent AI citation. For most businesses, reaching Level 3 (Topical Authority Entity) in the maturity model is the inflection point where AI citations begin appearing consistently. The entity SEO guide covers this framework in detail.

Our Approach: From Audit to Ongoing Optimisation

Our LLM Optimisation process follows a systematic methodology refined across multiple client engagements — from building the comprehensive healthcare IT content ecosystem for Coviant Software’s Diplomat MFT platform (generating 200+ enterprise leads through organic and AI-driven discovery) to developing criminal defence content strategies for Olliers Solicitors that capture both organic rankings and AI-generated answer citations.

Every engagement begins with an AI visibility audit: systematic testing of your target queries across ChatGPT, Perplexity, Google AI Overviews and Copilot to establish your baseline citation presence and identify competitive gaps. We then assess entity health, content architecture and structured data completeness before building a prioritised roadmap that addresses the highest-impact opportunities first.

The ongoing optimisation phase combines content strategy (comprehensive, authoritative content structured for AI extraction), technical implementation (structured data, entity consolidation, content architecture), and continuous monitoring (monthly AI citation audits, competitive analysis, strategy refinement). LLM Optimisation is not a one-off project — it is an ongoing discipline that compounds over time, with each month’s work building on the foundations established in previous months.

Who Benefits Most from LLM Optimisation

LLM Optimisation delivers the strongest returns for businesses where discovery and trust are critical to the sales process — typically B2B companies, professional services and specialist providers in competitive markets.

B2B and SaaS companies benefit because their target customers increasingly use AI platforms for vendor research and comparison. When a procurement manager asks Perplexity to compare managed file transfer solutions, being cited in that response is a direct pipeline opportunity. Our Coviant Software engagement demonstrates this: a systematic content ecosystem that positions the brand as a cited authority across AI platforms for healthcare IT, HIPAA compliance and managed file transfer queries.

Professional services firms — solicitors, consultancies, agencies — benefit because AI recommendations carry implicit endorsement. When someone asks ChatGPT “What should I look for in a criminal defence solicitor?” and the response references your firm’s expertise, that builds trust before the prospect ever visits your website. Our work with Olliers Solicitors applies this principle to criminal defence and motoring law.

Specialist providers in defined niches benefit because AI systems preferentially cite sources with deep, focused expertise. A niche specialist with comprehensive content and strong entity signals in their specific domain can achieve AI citation rates that generalist competitors with larger websites cannot match. This is the entity-driven advantage that makes LLM Optimisation particularly powerful for focused businesses.

Frequently Asked Questions
What is LLM Optimisation?

LLM Optimisation is the practice of ensuring your business is accurately represented and frequently cited by large language models (LLMs) like ChatGPT, Claude, Gemini and AI-powered search tools like Google AI Overviews and Perplexity. It is the umbrella discipline that encompasses AI Overviews Optimisation (AIO), Answer Engine Optimisation (AEO), Generative Engine Optimisation (GEO) and AI Citation monitoring. It combines elements of traditional SEO, structured data, entity building and content strategy specifically designed for how AI models discover, process and surface information.

What is LLM ranking?

LLM ranking refers to your brand's position and presence in AI-generated responses — whether AI systems cite, recommend or reference your business when users ask relevant questions. Unlike traditional organic ranking which positions your page in a list of ten results, LLM ranking determines whether your brand is included in the synthesised answer that AI platforms deliver directly to users. LLM ranking depends on entity authority, content structure, topical depth, source trustworthiness and the specific retrieval mechanisms each AI platform uses. Improving your LLM ranking is the core objective of LLM Optimisation.

How is LLM Optimisation different from traditional SEO?

Traditional SEO focuses on ranking in search engine results pages — competing for positions in a list of links. LLM Optimisation focuses on being cited and recommended in AI-generated answers — competing to be one of the sources an AI synthesises its response from. The foundations overlap significantly (strong content, authority signals, technical excellence), but LLM Optimisation adds specific requirements: entity authority for AI trust signals, structured data for AI parseability, content structured for extraction rather than just readability, and freshness relative to competing sources. The most critical difference is the role of entity recognition — AI systems need to trust the source entity before citing its content.

What is AI optimisation?

AI optimisation is the broader practice of optimising your digital presence for AI-powered platforms — a term that encompasses LLM Optimisation, AIO, AEO and GEO. It covers ensuring your content is discoverable and citable by AI systems including ChatGPT, Google AI Overviews, Perplexity, Microsoft Copilot, Claude and voice assistants. AI optimisation requires content that AI systems can extract and cite, entity signals that establish trust, structured data that communicates your information in machine-readable format, and ongoing monitoring of how AI platforms represent your brand.

Is LLM Optimisation worth investing in now, or should I wait?

Now is the optimal time. Search volume for AI optimisation terms is growing exponentially (LLM optimisation +600% YoY, GEO agency +1,300% YoY) but competition for LLM visibility is still relatively low. The businesses that establish their AI citation presence now will build a compounding first-mover advantage. The dynamic mirrors the early days of SEO: companies that invested in organic visibility in the mid-2000s built authority that competitors spent years trying to close. The same compounding effect applies to LLM ranking — early entity authority and citation history create advantages that accelerate over time.

How do I know if my business is visible to AI?

The simplest test is to ask. Query your brand name and your core service terms in ChatGPT, Perplexity, Google Gemini and Microsoft Copilot. Ask questions your potential customers would ask: "Who are the best [your service] in [your area]?", "What should I look for in a [your service]?", "Compare [your product] with [competitor]". If AI systems don't mention your brand, or mention it inaccurately, you have a visibility gap that LLM Optimisation addresses. Our AI visibility audit systematically tests 30-50+ priority queries across all major platforms to establish a comprehensive baseline.

What is the difference between AIO, AEO and GEO?

AEO (Answer Engine Optimisation) is the foundational discipline — structuring content to be surfaced as direct answers across all platforms including featured snippets, voice assistants and AI search engines. AIO (AI Overviews Optimisation) is Google-specific, targeting citation in Google's AI-generated summaries that appear in search results. GEO (Generative Engine Optimisation) targets AI-native search platforms like Perplexity and ChatGPT that generate cited, synthesised answers. The three disciplines share significant foundations but have platform-specific nuances. Most businesses need all three, implemented with shared AEO foundations and platform-specific AIO and GEO refinements.

How long does LLM Optimisation take to show results?

Results build incrementally across the four pillars. Featured snippet and PAA improvements (AEO) can show results within weeks for queries where you already rank well. AI Overview citations (AIO) typically improve over one to three months as content restructuring and schema implementation take effect. AI-native search citations (GEO) build over three to six months as entity authority strengthens and content depth accumulates. Comprehensive LLM visibility across a broad query set generally takes six to twelve months of consistent investment. The compounding effect is significant — early wins build the authority that accelerates subsequent citation gains.

Does LLM Optimisation replace SEO?

No — LLM Optimisation builds on and extends traditional SEO. Strong organic rankings remain the foundation: Google AI Overviews source primarily from pages that rank well organically, and domain authority influences AI citation selection across all platforms. LLM Optimisation adds a strategic layer that ensures your organic authority translates into AI visibility. The businesses with the strongest LLM ranking are those with strong organic foundations enhanced by entity authority, structured data and AI-specific content optimisation. We deliver both as an integrated strategy, not competing alternatives.

Can small businesses compete for LLM visibility?

Yes — often more effectively than large competitors. AI systems evaluate topical authority for the specific query, not just overall domain size. A specialist business with deep expertise and comprehensive content in a defined niche can achieve higher AI citation rates than a larger generalist competitor with shallow coverage across many topics. The key is focused entity authority: build deep associations between your brand entity and your specific expertise areas through comprehensive content, consistent structured data and authoritative external mentions. Our Entity Authority Maturity Model helps businesses of any size diagnose their current position and build a realistic roadmap to AI visibility.

Why hire a generative engine optimisation agency?

Generative engine optimisation requires a combination of skills that most SEO agencies don't yet have: structured data expertise, entity authority building, AI platform testing methodology, and an understanding of how different LLMs retrieve and evaluate sources. A specialist GEO agency brings tested frameworks, competitive intelligence across AI platforms, and the ability to measure what's actually working. The discipline is evolving rapidly — what worked three months ago may already be outdated. Working with an agency that focuses on this space means you benefit from insights gained across multiple client engagements and continuous experimentation.