New for 2026

LLM SEO Agency

Get Cited in ChatGPT, Perplexity, and Google AI Overviews

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How AI search is rewriting the rulebook

AI search is rewriting how buyers research B2B software and services. When a CTO asks ChatGPT for the best observability platform or a marketing director asks Perplexity for the top B2B SaaS SEO agency, the language model returns 3-5 named brands with cited sources — not 10 blue links. Traditional SEO ranks pages; LLM SEO earns brand mentions inside the AI's generated answer. That is the difference between being ranked and being chosen.

Three layers separate traditional SEO from generative engine optimization (GEO). First, entity SEO: AI assistants resolve queries to entities (your company, products, founders), not just keywords — your brand must exist in their knowledge graph with consistent attributes across the web. Second, citation real estate: LLMs cite listicles, comparison pages, Reddit threads, G2 reviews, and authoritative editorial sources during retrieval — being in those sources is what gets you cited, not just ranking #1 on Google. Third, direct answer engineering: AI search optimization rewards content structured for extractability — schema markup, FAQ optimization, comparison tables, and definitional snippets that an LLM can lift verbatim into its response.

Why now: citation real estate is being claimed monthly. Brands building entity foundations in 2026 compound for the next 3 years as AI search becomes the default interface for high-consideration B2B research. By 2027, Gartner estimates 50% of organic search traffic will be intercepted by AI Overviews and conversational search — pages without LLM visibility lose pipeline silently. Read more in our 2026 LLM SEO primer, or scroll to our 10-deliverable services grid below.

Our LLM SEO services — 10 deliverables for AI search visibility

AI & LLM visibility audit

Baseline your current AI visibility and citation footprint across ChatGPT, Perplexity, Claude, Gemini, Copilot, and Google AI Overviews. We map which prompts surface you, which name competitors instead, and which ai search engines you're invisible to today. The audit report becomes the foundation document the rest of the engagement is measured against.

Natural-language query & prompt research

Identify the 50-200 conversational prompts your B2B SaaS buyers ask AI assistants — the long-tail prompts that drive zero-click discovery. Our prompt research goes beyond traditional keyword tools; we model how a CTO, marketing director, or procurement lead phrases an actual purchase-intent query to a language model.

Entity SEO & brand entity development

Engineer your brand into the knowledge graph: consistent NAP signals, schema markup, Wikidata claims, founder and team entity bios, and structured attributes AI assistants resolve to. Brand entity development is the single highest-leverage layer of LLM SEO — without it, AI assistants cannot reliably identify you across prompts.

Schema markup & structured data (LLM-ready)

Service, Organization, FAQPage, HowTo, Product, and Article schema markup engineered for LLM retrieval — well beyond what traditional SEO tools generate. Our schema markup work targets the structured-data signals AI search engines actually parse during retrieval, including JSON-LD nesting patterns most plugins skip.

Direct answer engineering

Restructure content so an LLM can extract a clean, citable answer: definitional snippets, comparison tables, numbered lists, and FAQ blocks. Direct answer engineering is the bridge between traditional content optimization and the new citation-extraction patterns that ai search engines actually reward.

FAQ optimization for LLM responses

Mirror FAQPage schema body-to-JSON-LD 1:1 with the answer formats LLMs prefer to cite — short definitional answers paired with depth and supporting context. FAQ optimization is one of the fastest wins in any LLM SEO engagement; cleanly structured FAQs get cited within weeks of indexing.

Semantic content optimization

Topic-cluster mapping and semantic content gap analysis tuned to AI assistants — covering the entity-and-attribute space your category actually inhabits, not just keyword density. Semantic content optimization moves you from rank-tracking to citation-tracking as the primary success metric.

Listicle & reference audit

Audit which listicles, editorial references, G2 comparison pages, and Reddit threads LLMs cite for your category — then earn placement in those sources through outreach, contribution, and thought-leadership pitches. The listicle audit pattern is what separates Citation-First LLM SEO from generic content optimization.

RAG / vector-feed structuring

For SaaS with docs, help-centres, and knowledge bases: structure content as retrievable chunks with metadata that RAG pipelines and LLM retrievers can ingest cleanly. We optimise both your public surface (for crawler-driven retrieval) and your customer-facing AI assistants (for vendor-driven retrieval).

Citation monitoring & iteration

Monthly tracking across 6 ai search engines of which prompts return you versus competitors, with a quarterly iteration roadmap. Citation-First LLM SEO is measured, not vibes — every month you see exactly where ai visibility moved, which clusters compounded, and which prompts still need work.

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Realistic timelines and pricing for LLM SEO

Transparent ranges. No surprises after the discovery call. Citation-First LLM SEO is measured work that compounds across ai search engines — and we price it as such. First measurable citation uptick typically lands in 90-180 days; full compounding visibility takes 6-12 months.

Foundation

from $2,500

/ month

Audit plus entity foundation work. 90-day starter for solo founders and early Series A B2B SaaS brands ready to baseline ai visibility before scaling content.

AI visibility audit plus citation baseline across 6 ai search engines
Entity SEO and schema markup engineering (Organization, Service, FAQPage)
Brand entity development foundation (Wikidata signals, founder bios)
Top-priority direct answer engineering on 3-5 priority pages
FAQ optimization for LLM responses across priority pages
Monthly citation monitoring report with prompt-level deltas
Slack/email support with same-week reply SLA

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Most popular

Growth

from $5,500

/ month

Foundation plus scaled cluster work plus listicle and reference audit. Series A to B B2B SaaS brands scaling internationally and looking to compound ai visibility across 10-15 prompt clusters.

Everything in Foundation
Listicle and reference audit plus outreach to 10-15 sources
10-15 priority answer clusters engineered with semantic content optimization
Content optimization on 15-20 existing pages plus 4-6 new pages
Brand entity development at depth (Wikipedia work where appropriate)
Bi-weekly citation tracking dashboard with competitor delta
Quarterly iteration roadmap and executive strategy call
Prompt research extension to long-tail conversational search queries

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Enterprise

custom

Multi-market plus multi-language plus RAG and vector-feed engineering for B2B SaaS brands at Series B and above. Built for brands competing globally where ai visibility across regions and languages is mission-critical pipeline infrastructure.

Everything in Growth, scaled across markets
Multi-language entity SEO engineering (EN plus RU plus 1-3 EU languages)
RAG and vector-feed structuring for help-centres, docs, and knowledge bases
Custom schema markup for product catalogues and structured taxonomies
Cross-market citation building coordinated across regional listicles
Weekly executive reporting plus dedicated strategist (no juniors)
Custom prompt-monitoring tooling and integrations with your BI stack
Dedicated technical SEO support for ai search engine crawl optimization

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Engagement profiles — what an LLM SEO programme looks like

DevTools B2B SaaS (Series B)

Hypothetical engagement profile

Pre-revenue ICP misalignment in their core observability category; long-tail bottom-funnel keyword cluster underserved by existing content; zero ai visibility footprint across ChatGPT, Perplexity, and Gemini. Competitors already cited in 4 of 6 ai search engines for the category-defining prompts their CTO buyers were asking. The brand existed in Google's traditional search engines but was effectively invisible to ai assistants.

Target: 5-15 citations in ChatGPT and Perplexity for category prompts within 6 months

Target: 40-80% organic pipeline lift over 9-12 months alongside traditional SEO content optimization

Target: brand entity development and schema markup overhaul in first 90 days

We do NOT promise inflated sales multipliers or first-page guarantees in 30 days

Fintech / RegTech B2B SaaS (Series A)

Hypothetical engagement profile

Strong product, weak entity layer. Founder LinkedIn outranks the company itself in Gemini's entity resolution. Bottom-funnel comparison prompts (e.g. 'X vs Y' or 'best alternative to Y') return only competitors. Schema markup coverage below 30% of theme-supported types. The CMO had a great traditional SEO programme but the new generation of ai assistants was bypassing them entirely.

Target: rebuild entity SEO layer plus comparison-page citation coverage in 90 days

Target: presence in 8-12 listicles ai assistants cite for the RegTech category within 6 months

Target: full schema markup expansion to 8+ JSON-LD types per priority page

We do NOT promise first-page Google guarantees or zero-cost link building

B2B Professional Services / Consulting

Hypothetical engagement profile

High-consideration buyers research with ai assistants before booking discovery calls. The brand mentioned by name in only 1 of 6 ai search engines for category prompts. No structured FAQ coverage, no FAQ optimization, no branded methodology. Search engines still ranked them on Google for their main service but newer buyers were finding competitors via Perplexity and Claude during initial research.

Target: branded methodology plus FAQ optimization coverage live across 6 ai search engines within 90 days

Target: 3-5 listicle citations in 'best [category] consultancies' ai assistant prompts within 6 months

Target: schema markup, Service, and FAQPage JSON-LD on all priority pages

We do NOT promise inflated sales multipliers or instant pipeline doubling

Which AI engines we optimise for

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ChatGPT (OpenAI)

The largest of the ai search engines and ai assistants — sources answers via training data, web browsing, and custom retrieval through GPT search. We engineer entity SEO and brand entity development so your company is cited when B2B SaaS buyers ask category-defining prompts. ChatGPT is where most LLM SEO programmes show first measurable lift.

🔍

Perplexity

Cite-everything ai search engine — returns answers with numbered source links exposing exactly which references it pulled from. We optimise for the editorial and listicle sources Perplexity cites most often in your B2B category. Perplexity citations are also the easiest to track, making it an ideal early indicator of ai visibility.

🧠

Claude (Anthropic)

Strong on reasoning and synthesis among ai assistants. Tunes toward longer, more authoritative sources and rewards depth over breadth. We engineer definitional clarity, structured arguments, and schema markup signals into your content for Claude retrieval — particularly useful for high-consideration B2B SaaS purchases.

✨

Gemini (Google)

Tied to Google's index — overlaps with traditional search engines but layers entity understanding, schema markup parsing, and AI Overviews surfacing. Our Citation-First LLM SEO work doubles as Gemini optimization since the same entity signals feed both traditional SERPs and AI Overviews. Gemini citations compound with classic SEO gains.

💼

Copilot (Microsoft)

Bing-grounded with enterprise distribution baked into Microsoft 365. We optimise for Bing's index plus the entity signals Copilot prioritises for B2B SaaS buyers in enterprise procurement workflows. Copilot is undervalued by most agencies — the enterprise audience using it has higher purchase authority and longer contract values.

🎯

Google AI Overviews

The ai search layer most users see daily — intercepts 50%+ of high-intent queries on Google. We engineer content optimization, schema markup, and direct answer engineering for AI Overview extraction without sacrificing classic SERP visibility. AI Overviews are the largest single ai visibility surface for B2B SaaS in 2026.

Who LLM SEO is for

🚀

B2B SaaS scaling internationally

Series A-C B2B SaaS brands competing across US, EU, and APAC markets where ai search dominance creates compounding pipeline advantage. If you're scaling beyond a single geography, brand entity development is what keeps ai assistants resolving to one brand across markets.

💼

B2B services brands

Agencies, consultancies, and professional services with high-consideration sales cycles — buyers research with ai assistants before booking discovery calls. LLM SEO ensures your name appears when those buyers ask their AI for category recommendations.

🔬

Brands with strong existing SEO

If you already rank well on Google's search engines, LLM SEO is the next layer — entity SEO, schema markup at depth, and citation building on top of your foundation. Existing SEO equity actually accelerates LLM SEO results.

📊

CMOs and founders ahead of the curve

Leaders who see organic search shifting and want to be cited by ai search engines before competitors lock in citation real estate for the 2026-2027 buyer cohort. First-mover ai visibility compounds for years.

🌍

Multi-language / multi-market brands

EN+RU, EN+EU, or 3+ language B2B SaaS — we engineer entity SEO and brand entity development consistency across languages so ai assistants resolve to one brand, not fragmented language variants. Multi-language entity work is where most agencies fail; we ship it as a core deliverable.

Our Citation-First LLM SEO methodology

Step 1 — Visibility audit & current citation baseline

We run 100-200 prompts across 6 ai search engines (ChatGPT, Perplexity, Claude, Gemini, Copilot, Google AI Overviews) and document where you're cited, where competitors are cited, and which listicles and references surface in your category. Prompt research at this stage is exhaustive — natural-language query mapping, intent classification, and entity-resolution checks. You leave week 2 with a citation baseline report and an ai visibility scorecard — the foundation document the rest of the Citation-First LLM SEO engagement is measured against.

Step 2 — Entity foundation & schema engineering

We audit and rebuild your entity layer top-to-bottom: Organization, Service, Product, FAQPage schema markup, Wikidata and Wikipedia presence, founder and team entity bios, NAP consistency across the open web, and structured-data coverage of your full category vocabulary. Brand entity development is the layer ai assistants and ai search engines resolve to; without it, no amount of content optimization will produce reliable citations. This step typically lifts ai visibility within 6-8 weeks of completion.

Step 3 — Content & answer engineering

We restructure 10-20 priority pages (or build new ones from scratch) for LLM extractability: definitional snippets, comparison tables, FAQ optimization, semantic content completeness, and direct answer engineering throughout. Pages become citable assets, not just rankable URLs. Each priority page is engineered against the actual prompt research from step 1 — we know which prompts we want each page to answer, and we tune content optimization to win those specific extraction patterns.

Step 4 — Citation building (listicles, references, authoritative sources)

We earn placement in the listicles, editorial pieces, G2 and comparison sites, Reddit threads, and authoritative sources ai search engines cite for your category. Outreach plus contribution plus thought-leadership pitches — anchored to the audit data from step 1. The listicle and reference audit pattern is unique to Citation-First LLM SEO; most agencies stop at on-page work and never close the citation loop.

Step 5 — Monitoring, iteration, reporting

Monthly re-runs of the prompt panel show which ai search engines now cite you versus competitors, with delta tracking against the baseline. Quarterly iteration roadmap. Citation-First LLM SEO is measured work — you see exactly how ai visibility compounds month over month, which clusters are working, which need second-cycle optimization, and you get board-ready data to brief executives on the new AI search channel.

Frequently asked questions about LLM SEO

What is LLM SEO and how is it different from traditional SEO?

LLM SEO — also called LLMO (LLM optimization) or generative engine optimization — engineers your brand, content and schema markup so AI assistants and AI Overviews cite you when buyers use conversational search. Traditional SEO optimises page rankings for keyword queries; LLM SEO optimises brand citations for natural language query prompts.

Which AI engines do you optimize for?

Six: ChatGPT (OpenAI), Perplexity, Claude (Anthropic), Gemini (Google), Copilot (Microsoft) and Google's AI Overviews. Each AI engine has its own retrieval and citation behaviour, so a Citation-First LLM SEO programme tunes per engine. Some agencies group all six as AIO (AI optimization); we keep the engine-by-engine breakdown because tactics differ.

How long until I'm cited in ChatGPT / Perplexity?

90 to 180 days for first measurable citation appearances on a scoped prompt set, assuming the entity SEO foundation is in place by month two. Perplexity surfaces first (14 to 60 days) because its retrieval is most aggressive on real-time index. ChatGPT and Gemini lag. Compound effects appear in months 7 to 12.

Can you guarantee citations?

No. Any agency promising guaranteed citation in ChatGPT or guaranteed AI Overviews placement is over-promising. AI engines re-train continuously and citation decisions are stochastic. What we guarantee is the methodology: every step in Citation-First LLM SEO ships on time with reproducible measurement and transparent reporting.

Does LLM SEO replace traditional SEO?

No. LLM SEO is a layer on top of traditional SEO, not a replacement. Traditional search engines still drive most B2B organic traffic. The two share a foundation (schema markup, entity SEO, technical health) and diverge on optimisation surface. Most B2B brands keep investing in traditional SEO and layer LLM SEO on top.

How is this different from "AI content" or "AI writing"?

LLM SEO is about getting AI engines to cite you. AI content is about using AI to produce content faster. Different practices, different success metrics. We do not ship unedited LLM output; AI-ready content for LLM SEO is engineered by senior consultants and edited for citation-ready structure.

What's the relationship between schema markup and LLM citations?

Schema markup is the highest-ROI technical signal for LLM SEO. AI engines and retrieval augmented generation systems parse structured data far more reliably than prose. A page with rich validated schema markup is sliced into atomic citation-ready units. Service, Organization, FAQPage and Article are the most-cited types in our measurement.

How do I measure LLM SEO success?

Citation appearance per prompt per engine over time, against a month-one baseline. Secondary metrics: brand mention frequency, citation share-of-voice vs top three competitors, AI-sourced inbound count in the CRM, and AI Overviews CTR recovery for queries losing share to zero-click search.

What does an LLM SEO engagement cost?

Three tiers: single-engine focus from $3,500/month, 6-month minimum; multi-engine from $5,500 to $7,500/month, 9-month minimum; full LLM SEO programme from $9,500/month, 12-month minimum. No setup fees. We do not run sub-$1,500-per-month engagements — senior consultant time alone costs more.

Do you work with B2B SaaS brands specifically?

Yes — B2B SaaS is our primary vertical. Most engagements come from B2B SaaS brands with mature traditional SEO now investing in AI visibility as the next layer. Our prompt research, citation building and engagement profile templates are calibrated for B2B SaaS buyer patterns. We also work with B2B services and professional services; consumer brands we decline.

What is GEO and is it the same as LLM SEO?

GEO stands for generative engine optimization — optimising for generative AI engines and AI Overviews. GEO and LLM SEO are synonyms in our usage. UK agencies prefer GEO; US agencies prefer LLM SEO; an emerging cohort uses AIO. The work is the same: entity SEO, schema markup, content optimization, citation building. If you searched geo agency to find this page, you are in the right place.

Can you help recover citations if a competitor has locked them in?

Yes, with a longer horizon. Reclaiming citation real estate after a competitor has been canonical for 6+ months takes 12 to 18 months of brand entity development, listicle audit displacement, reference audit work, and direct answer engineering. The work compounds; the displacement is real; the timeline is longer than win-first.

Continue exploring our SEO services

🌐

SEO services

Our core SEO offering — keyword research, technical SEO, content optimization, schema markup, and link building for B2B SaaS and B2B services brands. This is the foundation layer that LLM SEO and AI search optimization build on top of.

Learn more →

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SEO services in Europe

EU-focused SEO programmes with hreflang, multi-language entity SEO, and GDPR-compliant analytics for 8 EU markets. The Europe page details our regional methodology for brand entity development across languages, including how we coordinate citation building cross-border.

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🇺🇸

SEO services in the USA

US-market SEO programmes for B2B SaaS and B2B services brands targeting English-speaking buyers in North America. Combines classic search-engine work with ai visibility programmes designed for the US buyer cohort and US-flavoured ai search engine prompts.

Learn more →

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SEO for ecommerce

B2B-First Ecommerce SEO for Shopify, WooCommerce, Magento, BigCommerce, and headless commerce stacks. Product-page schema markup, category clusters, and ai search visibility for ecommerce brands selling to B2B buyers and DTC audiences who research with ai assistants.

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SEO for B2B SaaS

Pipeline-First SaaS SEO for DevTools, Martech, Fintech, HRTech, Cybersec, and Vertical SaaS across Seed-A to Series C funding stages. Combines pipeline-attribution reporting with the same Citation-First LLM SEO entity and schema work to win both Google and ai search engines.

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Get cited by AI before your competitors lock it in

Citation real estate across ai search engines is being claimed monthly by the brands moving first on entity SEO and brand entity development. Foundations built in 2026 compound across ChatGPT, Perplexity, Claude, Gemini, Copilot, and Google AI Overviews for the next three years. Book a free LLM visibility audit — we baseline your current ai visibility across 6 ai search engines and ship you a Citation-First LLM SEO scorecard with a 90-day starter roadmap, no sales pitch. Citation-First LLM SEO • rebuilt 260522-fv1.

✓ No long-term lock-ins

✓ Transparent pricing ranges

✓ Direct strategist contact — no junior account managers

✓ Citation-First LLM SEO methodology shipped with every engagement

Book a free LLM visibility audit

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