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SEO

ChatGPT and LLMVisibility

Customers now ask chat assistants who to hire or buy from. We check what they say about you and strengthen the sources they rely on.

ChatGPT and LLM Visibility: what the work involves

Ask an assistant for the best accountant, supplier or software house in your city and you may discover that it names rivals, repeats outdated information about you or says nothing at all. Language models learn from training data and, in some products, retrieve live web results. Either way they lean on what is published about you: your own site, review platforms, directories, news and third-party mentions.

We run a structured set of questions customers might ask across the main assistants, record whether you appear and whether the description is right, and trace wrong or missing facts to their sources. Then we fix what you control: a clear about page, consistent profiles, accurate organisation data, helpful comparison and pricing-free explainer content, and corrections on third-party pages. Monitoring repeats the tests so you can see trends instead of anecdotes.

What we build

Core features

01

Prompt-set testing

A repeatable list of customer questions run across assistants, logging mentions, descriptions, sources and competitors named.

02

Source tracing

When an assistant states something wrong, we look for the page that likely feeds it and plan a correction.

03

Brand fact sheet

A single canonical description of who you are, what you do, where you operate and what you are known for, reused consistently across your site and profiles.

04

Citable explainer content

Clear, well-sourced pages answering the questions your buyers ask, written so a model or a person can quote them accurately.

05

Third-party presence

Accurate profiles on review sites, directories and industry sources that assistants commonly reference.

06

Retrieval access check

Robots, rendering and speed are verified so assistants that browse the web can read your key pages.

Planned for

What we get right before launch

Models can still be wrong

Even with perfect sources, an assistant may hallucinate or mix companies up. We document errors and improve inputs, but cannot edit a model directly.

Training data changes slowly

Corrections to your web presence may take months to appear in a model's built-in knowledge, though retrieval-based features can reflect changes sooner.

Do not fabricate authority

Fake reviews, spun mentions and manipulative prompt-stuffing are against platform rules and can backfire. We build presence from real, checkable sources.

Stack

Tools and technology

  • ChatGPT
  • Google Gemini
  • Perplexity
  • Google Search Console
  • GA4
  • Schema.org validator
  • Ahrefs
  • Bing Webmaster Tools
ChatGPT and LLM Visibility FAQ

Common questions, answered

Can I pay to be recommended by ChatGPT?

Not through an SEO service, and we would not promise it. Visibility comes from being a clear, well-referenced source. We can improve the inputs and monitor results, but recommendations remain the model's output.

How do I know what AI tools say about my business?

By asking them systematically. We prepare a set of realistic prompts, run them across several assistants at intervals and log what is said, because single answers are unreliable and vary from one run to the next.

Why does an assistant describe my company wrongly?

Often because a prominent page contains outdated or ambiguous information, or because another company shares your name. Tracing the source and publishing clearer, consistent facts is the practical remedy.

Is this different from normal SEO?

It overlaps heavily. Crawlable, authoritative pages and consistent entity data help both. The extra work is testing assistant answers, correcting third-party sources and writing content that is easy to quote accurately.

Ready to start your ChatGPT and LLM Visibility project?

Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.