ChatGPT, Claude, Gemini and Perplexity answer questions in your field every day — whether you sell something, run a public service or represent a sector. This check shows whether you get named, what stance the answers take, and which sources they rely on.
THE PROBLEM
As buying journeys shift from search results to AI conversations, insight disappears. Most companies have no idea whether they are recommended, ignored, or described from the wrong sources.
AI does not mention you when customers ask about your category. Competitors get the recommendation instead.
Models describe you from directories, old press, or third-party sites — not from your own content.
When AI ranks alternatives you land at the back. Without data it is impossible to prioritize.
WHAT YOU GET
Not a generic score. A snapshot of how the models that matter actually handle your brand.
Which models mention you when asked about your category — and which leave you out entirely.
We pull facts from your own domain and check whether what AI says matches, drifts, or contradicts.
Who gets pulled up ahead of you when AI compares alternatives in your category.
Concrete signals on what to fix first — content, entity signals, or authority.
The accuracy score uses your website as ground truth. For full per-prompt fact-checking — with your own curated ground truth and drift alerts over time — you need the paid Entity Accuracy Engine.
HOW IT WORKS
Questions follow your organisation’s role and selected focus: visibility, reputation or factual accuracy.
Name, domain, category, business type. We tailor the prompts and models to your situation.
A handful of realistic question variants across multiple AI models. In parallel we read your own website to have something to compare against.
Visibility, accuracy, sources, and competitors — plus clear signals on what to fix first.
No commitment — just insight you cannot get from Analytics or Search Console.
Start free checkVisibility tests whether you are mentioned without being named in the question. Reputation asks directly about your organisation and examines the tone of the answer. Factual accuracy compares claims with the information available on your website. These are different tests, not three labels for the same score.
Review the questions, models and cited sources alongside the result. A small set of answers is not a complete account of public opinion or a definitive fact check. If your website blocks the crawler, the report cannot use its content as a reliable comparison source. Recurring monitoring belongs in the broader 3LA workflow.
FROM THE BLOG

LLMs hallucinate about companies, prices, key people and mandates - and it's costing NGOs, universities, research bodies, financial institutions, political actors and agencies real leads and real trust. Here's the background of the Entity Accuracy Engine, and exactly who I built it for.

Classical AI SEO tools grade your content with an LLM. The Three-Layer Approach measures - deterministically - whether AI can find, trust and cite you. Here's the honest comparison. This article was first published on nettpilot.com

ChatGPT, Claude, Perplexity and Gemini do not share a user base. They share a category name. A 2026 study found only ~11% of domains cited by ChatGPT are also cited by Perplexity. Here is the field guide to a platform-segmented GEO strategy.