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LLM SEO

Your brand, represented correctly in every language model that matters

LLMs are consulted for vendor comparisons, buying decisions, and category research millions of times a day. How they describe your brand is determined by the sources they trust — and we influence those sources.

Site health score96 / 100
Core Web VitalsPassed
Crawl efficiency91%
Indexation88%
+0%
accurate LLM brand mentions
0×
positive framing in model outputs
+0%
high-trust source coverage
0+
LLMs audited and optimised
The problem we solve

LLMs may already be misrepresenting your brand

Language models form their understanding of your brand from training corpora, web retrieval, and the third-party sources they weight as authoritative. Outdated press, competitor-written comparisons, and thin third-party coverage can leave models describing your product inaccurately — or not at all. You don't get a chance to object to an AI's answer.

[ LLM brand representation score ]
What's included

What LLM SEO covers

LLM brand audit

We systematically query major LLMs with hundreds of brand and category prompts, documenting how your brand is currently described, compared, and recommended.

High-trust source acquisition

LLMs heavily weight Wikipedia, major publications, and authoritative industry sources. We secure placements and corrections in the sources that shape model outputs.

Training-signal content

We produce and distribute content that functions as a reliable signal about your brand — clear, factual, consistently framed across every surface a model might ingest.

Digital PR for model training

Press coverage in model-trusted outlets creates a consistent, authoritative narrative about your brand that persists through model updates and retraining cycles.

Entity disambiguation

If your brand shares a name with another entity, we build the disambiguation signals LLMs need to distinguish you correctly and cite the right information.

Representation monitoring

We run monthly LLM audits to track changes in how models describe your brand — catching regressions early and measuring improvement over time.

Our methodology

From misrepresented to model-preferred

1

Audit current LLM representation

We query six major LLMs across 150+ prompts covering your brand, products, competitors, and category — producing a detailed map of what models currently say and where they're wrong or missing.

2

Build the authoritative source layer

We execute a targeted digital PR and content distribution program to place accurate, authoritative brand information in the specific sources LLMs weight highest when forming their understanding.

3

Monitor and maintain accuracy

LLMs update continuously. Monthly audits track whether representation has improved, identify new inaccuracies introduced through model updates, and keep your program current.

Proof it works

How a technical overhaul unlocked 187% more revenue

A fast-growing marketplace was leaking authority through duplicate URLs and slow templates. We re-architected crawling, halved load times, and rebuilt their internal linking.

  • 2.4× faster pages across the catalog
  • 63% more product pages indexed
Read the case study
+0%organic revenue in 6 months
Service FAQ

Questions, answered

Directly editing an LLM's weights is not possible. But LLMs form their outputs from the sources they retrieve and from training data — and those sources are influenceable. By building a consistent, authoritative, high-source-quality narrative, we shift how models represent your brand over time.
Traditional reputation management targets search results pages and review sites. LLM SEO specifically targets the sources and signals that language models use to form answers — a different technical surface with different tactics, even if the strategic goal of accurate brand representation overlaps.
It depends on the model. Some LLMs with frequent web retrieval (like Perplexity) can reflect new sources within days. Training-data-dependent changes in models like GPT-4o take longer — typically tied to model update cycles, which can be months. We pursue both tracks simultaneously.
This is increasingly common. Our audit identifies the specific sources driving inaccurate model outputs, and we counter with authoritative content and direct source corrections. In cases involving defamatory content, we also work with legal counsel as part of a coordinated response.

Get a free technical SEO audit

We'll show you exactly what's holding your site back — and the revenue you're leaving on the table.

Claim your free proposal
  • Prioritized list of your highest-impact fixes
  • Competitor benchmark of your site health
  • A revenue forecast for getting it right