LLM SEO: being the source the model quotes

Q: What is LLM SEO?

A: LLM SEO is the practice of getting a large language model to cite and recommend your brand in its answers. The model returns one synthesised answer rather than a ranked list, so the unit of success is a citation rather than a position.

LLM SEO is optimising for the model rather than the index. A language model does not return ten links, it returns one answer built from a handful of sources, so the goal changes from ranking to being quoted. That means clear factual statements the model can lift, structured data it can verify, and consistency across the third party pages it reads. Sophyx measures which prompts you lose, writes the fix, and publishes it.

See which prompts you lose Generate your llms.txt free

Thirty prompts, re-checked every two weeks, free forever
llms.txt, robots.txt and per-page JSON-LD generated for you
The finished page published to your own domain

Free forever measurement, done for you implementation. Canadian company, Canadian hosting. Your data stays in your own silo, with no cross-tenant learning.

A model reads your page more often than a person does

Of this site's own zero-click search terms, 122 of 158 have no measured human search volume at all. Most of that traffic is a model expanding one question into variants. There was never a searcher to win a click from, which means a sentence a model can lift and attribute is worth more than a paragraph that ranks.

Your best answer is buried under three paragraphs of setup, so nothing gets lifted.

The fact the model needs is on the page, but nothing makes it verifiable.

A competitor wrote the same thing more plainly, so they get quoted.

See what AI says about you now

What we generate and publish

Every platform in this category ends at a recommendation you still have to implement. Read from each vendor’s own published pages on 19 September 2026, none of them can put a page live on your domain. That is where our work ends.

Pages rewritten so a model can lift a self-contained statement and attribute it

Per-page JSON-LD, generated rather than hand-maintained

A generated llms.txt and robots.txt, validated before they go live

Your brand knowledge graph, so entities and relationships are explicit

Prompt level testing on a schedule, with the answers captured as text

Publishing from the AI assistant your team already uses, over our MCP server

How the engagement runs

About 30 minutes to set up and about an hour a month to run. You approve every draft before it goes live. Nothing publishes on your behalf without a yes.

1
Measure which prompts you lose
Thirty prompts, re-checked every two weeks, free forever on the free plan. No card. This is the diagnosis and we do not charge for it.
2
Find what the model could not use
Usually one of four things: no clear statement, no verifiable fact, no structured data, or a third-party source saying something different.
3
Rewrite to be quotable
A direct answer near the top, plain language, and the structured data that lets the model check it. Pages written this way tend to read better to humans too.
4
Publish it
Live on your domain, with the generated llms.txt and JSON-LD. You approve the draft first, every time.
5
Re-run and compare
The same prompts on the same cycle, with the old answer next to the new one.

Start scoped, then run it monthly

Sprint one, fixed scope

Prompt set baselined, answers captured as text
llms.txt and robots.txt generated and validated
Per-page JSON-LD generated for the pages that matter
First rewrites drafted, approved and published
Knowledge graph built from your site

Then monthly

Prompt set re-run and compared to the baseline
New pages written and published each cycle
Structured data kept current as the business changes
Publishing available from ChatGPT or Claude over MCP
A weekly working session with our technical team

What we guarantee

Publish everything we write. If no major AI assistant has sent you a measured visit in 14 days, we keep working at no cost. If you are not showing up in at least one AI engine after 30 days, you get your money back.

See platform pricing

Who this is built for

Founder-led teams

Owners get the calls an assistant was sending to someone else, without hiring anybody to chase them. About 30 minutes to set up and about an hour a month to run. No new hire, and no retainer whose output you cannot read.

Agencies and consultants

Agencies add a line their clients can see in the calendar, across every client, without adding headcount. White-label reporting, every engine on every tier, and a weekly working session with our technical team so delivery never sits on one person.

In their words

What the people who run this say

I've been spending more time with Sophyx lately, and one thing I really like is that it does not just tell you “AI search matters.” It actually shows you where your brand stands. For years, SEO was mostly about ranking on Google. That still matters. But now businesses also need to ask: “Does AI understand my brand well enough to recommend it?” That is where tools like Sophyx become very useful. AI search is still early, but I think this is where a lot of visibility work is heading.

Mark O'Coin

SEO & AEO Strategist, Owner, Motif Design

Questions people ask before they buy

What is LLM SEO?

LLM SEO is the practice of getting a large language model to cite and recommend your brand in its answers. It differs from search engine optimisation because the model returns one synthesised answer rather than a ranked list, so the unit of success is a citation rather than a position.

Is there an LLM SEO tool, or is it all manual?

Both. The measurement is tooling: run a fixed prompt set on a schedule and record which answers name you. The fix is partly generated and partly written. Sophyx gives the measurement away free, 30 prompts re-checked every two weeks, and charges for the implementation.

Does llms.txt actually do anything?

It is a signal, not a guarantee. It tells a crawler where your clean, machine readable content lives. It will not make a model recommend you on its own, and anyone promising that is overselling it. It is cheap to publish and it removes one excuse for being misread.

How does this relate to traditional SEO?

It sits on top of it. Most of the pages a model reads are the pages Google already indexed, so good SEO is an advantage. We do not tell people Google is finished, because for most of our customers it still sends the majority of traffic.

What does the tooling actually measure?

We measure how you appear in AI web search answers through a GPT-5-class model with live web search, up to 30 prompts per cycle. That is the honest scope. We do not cover Meta AI or DeepSeek, and we would rather say so than let you find out later.

See which prompts return a competitor instead of you

Thirty prompts, re-checked every two weeks, free forever on the free plan. No card. See which answers name a competitor before you talk to anyone.

See which prompts you lose Send us your domain instead