LLM visibility: help AI models describe your brand correctly
Ask an AI assistant about your company and it may get your services, location or founder wrong, or confuse you with someone else. We build the consistent entity signals models rely on and monitor what they say about you.
LLM Visibility Optimization
Large language models form a picture of a brand from everything they have seen: your site, directory listings, social profiles, press, reviews and knowledge bases. When those sources disagree on your name, what you do or where you are, models hedge, leave you out or fill the gaps with guesses. This is a different problem from ranking a page. It is about whether a model recognizes you as a distinct, well-defined entity.
We start by asking the main models about you and your category and recording exactly what they say. Then we audit the sources behind that picture and make them agree: your About page, Organization schema with sameAs links to your official profiles, business directories, founder and team bios, and Wikidata where your organization meets its notability rules. For local businesses, consistent name, address and phone details matter as well.
Some models answer from training data, others search the web live, and most now do both. Corrections to live sources can show up sooner in search-connected answers, while training data changes on each provider's own schedule. We monitor answers across models over time so you can watch the picture improve instead of taking it on trust.
What You Get
Model answer baseline
We ask ChatGPT, Claude, Gemini, Perplexity and Microsoft Copilot a consistent set of questions about your brand, people and offerings, and log accuracy, tone and the sources they cite.
Entity home page
We make your About or company page the clear, authoritative description of who you are, with legal and trading names, founding date, leadership, locations and services stated plainly.
Organization and Person schema
We implement Organization, Person and related markup with sameAs links to your official profiles, so search engines and models can connect scattered mentions of you to one entity.
Knowledge graph signals
We check how you appear in Google's Knowledge Graph and, where you meet the notability criteria, help create or correct a Wikidata item with properly sourced statements.
Profile and listing consistency
We align names, descriptions, addresses, phone numbers and bios across directories, social platforms and industry listings, and flag outdated pages that keep old facts alive.
Ongoing answer monitoring
We rerun the question set on a schedule, track changes for each model and alert you when an answer becomes inaccurate or a competitor starts appearing in your place.
Our Process
Ask the models
We record what each major model currently says about you, your people and your category, including mistakes and missing facts.
Trace the sources
We find where those statements come from: your own pages, old listings, press coverage, reviews or knowledge bases.
Fix the record
We update your site and schema, correct or claim external profiles, and prepare factual material for the sources you do not control directly.
Monitor
We repeat the questions over time and report accuracy and visibility trends for each model you care about.
Deliverables
- A model-by-model report of how your brand is currently described, with errors highlighted
- A canonical brand fact sheet covering names, descriptions, leadership, locations and services
- Organization and Person structured data with verified sameAs links
- A profile and listing correction log showing what was changed and where
- A Wikidata item created or corrected where your organization is eligible
- Scheduled answer-monitoring reports across your chosen models
Tools & Platforms
We pick tools for your project, not the other way round. If you already use a platform, we work inside it.
Related Results
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LLM Visibility Optimization: Questions Answered
Can you change what ChatGPT says about us?
Not directly. No one can edit a model's answers. What we can do is make the sources that models learn from and search consistent and accurate, which gives them better material to work with. Search-connected answers often reflect fixes sooner; answers that rely on training data change when the provider updates the model.
Do we need a Wikipedia or Wikidata entry?
Not necessarily. Wikipedia has strict notability rules, and we do not write promotional articles for it. Wikidata is more open but still expects verifiable, sourced facts. If you qualify, a well-sourced Wikidata item helps connect your entity. If not, consistent schema, profiles and third-party mentions still do most of the work.
What affects the cost?
The number of brands, people and locations involved, how many listings need correcting, how many models we track, and whether you want ongoing monitoring. We agree a fixed scope and price up front, with monitoring offered as a separate recurring option if you want it.
What do you need from us?
Your official brand facts, a list of the profiles and listings you own along with access or a contact who has it, any past names or addresses, and the competitors you are usually compared with. Passwords stay with you; wherever a platform allows it, we work through delegated or team access.
Often Paired With
Generative Engine Optimization (GEO)
Make your pages the source ChatGPT, Gemini, Claude and Perplexity pull from when they answer questions in your industry.
Explore GEOAI Visibility Audit
A measured report of how often AI tools mention you versus competitors, and a prioritized plan to close the gap.
Explore AI Visibility AuditSchema & Structured Data
Product, FAQ, Article, Organization and local schema so Google and AI engines understand every page.
Explore Schema & Structured DataLet's Talk About LLM Visibility Optimization
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