LLM SEO · Large Language Models

Be what themodel knows.

I run LLM SEO for B2B SaaS — shaping what large language models know, retrieve and recommend about you, so ChatGPT, Claude, Gemini and Perplexity name you, not a competitor.

Book an LLM SEO audit →See what I do

SEO for the models, not just the index.

Model KnowledgeLive
KnowledgeModeled entity
RetrievalOptimized RAG-ready
RecommendationTracked share of voice
SourcesStrengthened authority
Experience across
Netpeak GroupAcademyOceanDataImpulseGoogle for StartupsSaaSFintech
01 / The shift

Models recommend brands. Are you one of them?

When a buyer asks an LLM for the best tool in your category, it answers from what it knows and what it retrieves. If your brand is fuzzy or absent in that knowledge, you are never in the recommendation.

01

You are not in the training knowledge

Models learn from the public web. If your entity and content are thin or inconsistent, the model has little to recall about you.

02

Retrieval skips you

Even with live retrieval (RAG, web tools), models pull from a few trusted, well-structured sources. Unstructured pages get passed over.

03

Competitors own the recommendation

If rivals are clearer and better-cited, the model recommends them by default, framing the buyer's shortlist without you.

The point of view

LLM SEO is about being known, then being retrieved.

Two layers win with language models: the knowledge they carry from training, and what they retrieve live at answer time. Both reward the same things - an unambiguous entity, structured machine-readable content, and authority across sources. I build that so models both recall and retrieve you. It overlaps with generative engine optimization - LLM SEO is the model-knowledge lens on it.

02 / What I do

LLM SEO, end to end.

The work that makes language models know, retrieve and recommend you.

Knowledge Audit● Scoped

Model knowledge audit

What ChatGPT, Claude, Gemini and Perplexity currently know and say about you, versus competitors.

Entity Modeling● Built

Entity & knowledge modeling

Make your brand unambiguous to models: entity definition, schema, and consistent facts across the web.

Retrieval Content● Built

Retrieval-ready content

Structured, liftable content that retrieval systems and RAG pipelines can find and quote cleanly.

Authority● Built

Source authority

The third-party mentions and citations that make models trust and repeat your information.

Recommendation● Built

Recommendation positioning

Frame your category and strengths so models name you when buyers ask for the best option.

Monitoring● Live

Model monitoring

Track what each model knows and recommends over time as they retrain and re-retrieve.

03 / Process

How an LLM SEO engagement runs.

1

Audit the models

Find what each major LLM knows and recommends about you and your category today.

2

Model the entity

Fix entity clarity and structured data so models have clean, consistent facts to recall.

3

Feed retrieval

Ship retrieval-ready content and build the authority that gets you pulled into answers.

4

Monitor & adapt

Track knowledge and recommendations across models and adapt as they retrain.

If the model does not know you, it cannot recommend you.
// Andrii Byzov — AI-native fractional CMO
4×REVENUE GROWTH YoY (operator track record)
5×LOWER CAC DELIVERED
15+ yrsFINTECH & SAAS, AI-NATIVE
Andrii Byzov, AI-native fractional CMO and LLM SEO specialistAndrii Byzov  /  LLM SEO
Who runs it

An operator who speaks model.

I am Andrii Byzov — an AI-native marketing operator who has led growth across B2B SaaS and fintech, including CMO roles at DataImpulse and AcademyOcean (Netpeak Group).

LLM SEO sits inside my broader AI search optimization work. I build model knowledge and retrieval as a system and run it hands-on, and write about it on my blog.

AI-nativeSINCE THE GPT ERA
0→14TEAM BUILT & LED
SoloOPERATOR-LED, NOT AN AGENCY
04 / Fit

Is LLM SEO worth it for you yet?

A strong fit if

  • +You are a B2B SaaS or technology company whose buyers ask LLMs for recommendations.
  • +Models barely know you, or describe you wrong.
  • +You want to be known and retrieved, not just rank on Google.
  • +You see AI recommendations becoming a real buying channel.

Not a fit if

  • −You expect to control exactly what a model says - no one can.
  • −You have no website authority or content to build on yet.
  • −You want a one-week hack, not a compounding asset.
  • −Your buyers never use AI tools to research.
05 / FAQ

LLM SEO, answered honestly.

What is LLM SEO? +
LLM SEO is optimizing so large language models - ChatGPT, Claude, Gemini, Perplexity - know, retrieve and recommend your brand. It works on both the knowledge models carry from training and what they retrieve live at answer time.
How is LLM SEO different from regular SEO? +
Classic SEO optimizes for ranking links on Google. LLM SEO optimizes for being part of a model's knowledge and its retrieved sources, so it names and recommends you. It leans on entity clarity, structured content and source authority.
Can you control what an LLM says about us? +
No one can fully control a model's output. The work improves your odds of being known accurately and recommended - by making your entity clear, your content retrievable and your authority strong - then measuring it over time.
Is LLM SEO the same as GEO? +
They overlap heavily. GEO is visibility inside generative engines; LLM SEO is the same shift viewed through what the underlying models know and retrieve.
How do you measure it? +
By tracking what each model knows and recommends across buyer prompts, share of voice versus competitors, and referral traffic from AI tools over time.
Start here

See what the models say about you.

An LLM SEO audit shows what ChatGPT, Claude, Gemini and Perplexity know and recommend today - and how to become the answer.

Book an LLM SEO audit →

Operator-led · AI-native · B2B SaaS