Visus Dictionary

LLM discoverability

LLM discoverability is how reachable and parseable your business facts are to large language models and retrieval systems that ground answers on the web.

Why it matters

If crawlers or extractors cannot read your offer, models fill gaps from competitors or generic training data.

How Visus measures it

Visus proxies discoverability via crawl success, text extraction coverage, structure, and corroboration—not via private model internals.

Example

If your prices and services only render after JavaScript, a retrieval system may fetch an empty shell and fall back to competitors. Server-rendering the same facts makes them discoverable.

Common misconception

LLM discoverability is not about being in a model’s training data. Most assistants ground answers on live, retrieved web content, so what matters is whether your current page is crawlable and parseable right now—not whether you were scraped years ago.

Related terms

• AI visibility
• Entity clarity
• AI citation

FAQ

• Does blocking AI crawlers in robots.txt affect discoverability?

  Yes. If you disallow the crawlers that answer engines rely on, retrieval systems may not be able to read your facts, and you can be left out of grounded answers even when your content is strong.

• How do I check if my facts are discoverable?

  View your page with JavaScript disabled, or fetch its raw HTML. If your key facts—offer, pricing, location, proof—are missing from that view, they may be invisible to retrieval systems too.

Cite this definition

Visus AI Visibility Dictionary. “LLM discoverability.” https://getvisus.com/ai-visibility-dictionary/llm-discoverability