AI Search Optimization –
Get Cited by AI. Get Found by Humans.

AI Search Optimization, also known as Generative Engine Optimization (GEO), is the practice of structuring your content so that AI-powered search engines—Google AI Overviews, ChatGPT, Perplexity, and others—cite, recommend, and surface your brand. Unlike traditional SEO which optimizes for blue links, GEO optimizes for AI-generated answers, citations, and recommendations.

LLMO is the strategy of making your brand, products, and content recognizable and citable by large language models (LLMs) like GPT, Gemini, and Claude. It involves entity definition, structured data, authoritative content creation, and ensuring your information appears in training data and real-time retrieval systems (RAG). LLMO is a superset of GEO—it covers all AI systems, not just search.

Google AI Overviews use AI to synthesize answers from multiple sources and present them at the top of search results. To be cited, your content needs: clear definitions, structured Q&A blocks, authoritative E-E-A-T signals, proper schema markup, and entity-rich content that directly answers user questions. Alice Labs optimizes content specifically for AI Overview inclusion.

Traditional SEO optimizes for ranking blue links on page one. AI Search optimization focuses on being cited in AI-generated answers. The key differences: 1) Content must be machine-readable and semantically structured. 2) Entity relationships matter more than keyword density. 3) Authoritativeness and source credibility drive citations. 4) Structured data and schema markup are critical for AI comprehension.

Yes. We optimize for all major AI search platforms including ChatGPT (with web browsing), Perplexity, Google AI Overviews, Microsoft Copilot, and Claude. Each platform has different retrieval mechanisms, but the core principles are the same: authoritative content, clear entity definitions, structured data, and citable claims with sources.

Results depend on your starting point and industry. Typical outcomes include: increased brand mentions in AI-generated answers, higher citation rates in AI Overviews (we track this), improved organic visibility as AI search grows, and stronger brand authority signals. Early movers gain disproportionate advantages as AI search market share increases.

We use proprietary monitoring to track: AI Overview inclusion rates, brand mention frequency in LLM responses, citation quality and context, competitor citation comparison, and the traffic impact of AI search referrals. We also monitor your entity graph strength and structured data completeness.

An entity graph is a connected network of concepts, people, products, and relationships that AI systems use to understand your brand. A strong entity graph means AI models know who you are, what you do, and when to recommend you. We build entity graphs through structured data, consistent content, authoritative backlinks, and knowledge base optimization.

Absolutely. AI Search and traditional SEO are complementary, not competing. Traditional SEO builds the foundation—domain authority, content depth, technical excellence—that AI systems rely on for citations. We recommend a combined strategy: traditional SEO for the base, GEO/LLMO for the emerging AI search layer. The best-positioned brands invest in both.

Start with an AI Search Audit (1-2 weeks) where we analyze your current AI visibility, map your entity graph, audit your structured data, and benchmark against competitors. We then create a prioritized roadmap: quick wins (schema, content restructuring) and strategic initiatives (entity building, authority content). No long-term contracts required.

An AI search visibility consultant audits how often AI engines (ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, Claude) cite your brand, identifies the queries where competitors are cited instead, and engineers the content, schema and entity signals needed to flip those citations. Alice Labs combines four disciplines in one role: classical SEO, entity SEO, structured data engineering, and LLM-citation tracking. Deliverables include a citation baseline, a prioritized intervention roadmap, monthly citation lift reports and content templates your team can scale.

A classical SEO agency optimises for blue-link rankings on Google. An AI search optimization consultant optimises for citation inside AI answers — a different target with different mechanics. Three concrete differences: (1) The unit of success is a citation, not a position. (2) The optimisation surface is the entity graph and JSON-LD, not the title tag. (3) Measurement requires LLM probing tooling, not just Search Console. Alice Labs runs both disciplines side by side so existing organic traffic compounds with AI-cited traffic instead of cannibalising it.

Yes. We work with European management consultancies, B2B SaaS, professional-services firms and enterprises across the EU and UK. Our LLMO programme handles multilingual citation tracking (English, Swedish, German, French, Spanish), GDPR-compliant data handling, EU AI Act alignment for in-product AI features, and entity-graph work tuned for European Wikidata, regulator pages and industry associations that LLMs weight heavily.

An LLMO agency engineers your brand to be cited by Large Language Models — ChatGPT, Claude, Gemini, Perplexity and Microsoft Copilot. Perplexity is particularly citation-friendly because it shows source links inline, which makes its optimisation playbook the cleanest leading indicator for all LLMs. Our Perplexity playbook covers: clean canonicalisation, sectionAnswer-style content, citation-worthy original data and statistics, schema completeness, and authority backlinks from the small set of domains Perplexity over-indexes on.

LLMO consulting is typically scoped in three sizes. (1) Audit — 1 to 2 weeks, baseline citation report, entity graph map, prioritized roadmap. (2) Programme — 12 weeks, audit plus implementation across priority topic clusters, monthly citation tracking. (3) Retainer — ongoing content restructuring, citation monitoring, entity authority building. We do not require long-term contracts and price on scope rather than headcount, so the same fee buys you senior LLMO expertise rather than a leveraged team.

Yes. Google AI Overviews (formerly SGE) is one of the most important LLMO surfaces because it sits on top of organic Google traffic. Our Google-specific LLMO work covers: HowTo, FAQPage, DefinedTermSet and Article schema implementation; sectionAnswer block engineering; E-E-A-T author signals; topical authority hubs; and structured-data audit of every priority page. We track AI Overview inclusion separately from blue-link rankings so you see both effects.

When evaluating an LLMO consultant or agency, ask four questions. (1) Can they show citation tracking across at least four LLMs (ChatGPT, Perplexity, Gemini, Claude), not just Google AI Overviews? (2) Do they engineer schema and entity graphs in-house, or sub-contract to generic SEO teams? (3) Can they share before/after citation lift on real clients? (4) Do they understand both classical SEO and LLMO, so the two compound rather than fight? Alice Labs is built around all four — but the questions are the right ones regardless of who you hire.

The LLMO tooling category is still nascent. The platforms most worth tracking are: Profound and Goodie for citation monitoring, Otterly.ai and Athena for LLM brand visibility, Surfer SEO and SEMrush for entity-driven content, schema.org and Schema App for structured data, and direct API probing of ChatGPT, Perplexity and Gemini for ground-truth measurement. Alice Labs uses a hybrid of off-the-shelf platforms and proprietary LLM probing so citation tracking is comparable across vendors and across time.

Schema and content restructuring changes can show up in Perplexity and ChatGPT citations within 2 to 6 weeks because both pull from live retrieval. Google AI Overviews typically lag 6 to 12 weeks because they depend on Google's index refresh and quality re-evaluation. Brand-level entity authority (Wikipedia, Wikidata, industry knowledge bases) compounds over 3 to 9 months. We commit to a measurable citation lift inside 90 days for in-scope priority topics, with monthly reporting from week 4 onward.

Google LLMO services optimize a brand for citation inside Google AI Overviews and the Search Generative Experience — the LLM-driven surface sitting on top of Google's classical index. Typical scope covers FAQPage, HowTo, Article, DefinedTermSet and Organization schema, sectionAnswer content engineering, E-E-A-T author signals, entity graph hygiene and structured-data auditing. Alice Labs runs Google LLMO alongside classical SEO so AI Overview inclusion and blue-link rankings compound instead of competing, with citation tracking reported separately for each.

LLMO consulting is the strategic and technical work of getting a brand cited by large language models — ChatGPT, Perplexity, Gemini, Claude and Copilot. A consultancy typically leads with senior expertise, audit, prioritization and hands-on schema and content engineering; an agency layers scaled production on top. Alice Labs is a Stockholm-headquartered LLMO consultancy with 100+ production AI implementations since 2023, senior-only delivery and transparent scope-based pricing, structured so European enterprises get partner-level attention on the citation and entity architecture rather than a leveraged team.

An AI visibility consultant measures brand presence across the four LLM surfaces (ChatGPT, Perplexity, Gemini, Google AI Overviews), diagnoses whether the gap is indexability, entity ambiguity, schema, retrieval or authority, and prioritizes fixes accordingly. In-house SEO teams typically own Google Search Console but have no LLM probing pipeline, no Wikidata or entity graph program, and no schema audit at the JSON-LD level. Alice Labs supplies the probing infrastructure, the entity graph work (Wikidata Q-IDs for founders and organization) and the schema-audit pipeline in-house teams rarely have time to build.