Use case Entities

Build an entity graph
of your own site

Answer engines retrieve fragments of your content and infer who you are, what you offer and how it connects. Moose builds that graph from the pages already crawled on your computer, marks which connections your pages state and which he inferred, and reads it in any later chat.

Watch Moose build one What comes back
Chat Workflows
Fathom Analyticshttps://usefathom.com
New chat
Home Inbox Context Visibility Workflows Audio Chats Artifact Library Connections
Recents
can you create an entity gra…Chat · now do we cover the topic of usi…Chat · 16m Building a Knowledge Grap…Content brief · 24m How AI Search Ranking Wor…Content brief · 2h
Sam SamPremium
can you create an entity gra… New chat Share
can you create an entity graph of usefathom?

On it, Sam. Let's map how Fathom's entities connect across the site.

I can build an entity graph for this project. Choose how deep the run should go, then start it below.

Build the entity graph

Hi, Moose maps the people, products, places, and topics across this project's crawled pages, plus how they connect.

Depth
QuickStructured data only. Runs instantly.
FullAdds an AI pass over your top pages. This can take a few minutes.
Reading 418 crawled pages. Last completed crawl: 8/2/2026. Build entity graph
Extracting entities from crawled pages (418/418)… Mapping how entities connect across pages… Assembling the graph…
Entity graph
Entities across this project
Quick
Entities
290
Relations
612
Generated
8/2/2026
3 labeled · 88 shared-page · 521 semantic
Entities by type
topic: 284 · organization: 3 · product: 2 · person: 1
Top entities
NameTypePagesSalience
User Documentation topic 246 7.12
Fathom Analytics product 22 4.20
Affiliate Program Terms topic 7 3.58
Fathom Analytics organization 10 3.43
Jack Ellis person 9 3.33
The exports include 285 more entities. Export CSV Export PDF
Share a URL, a draft document, or run an AEO audit…
Claude Sonnet 5.5 Send
Hi, Moose 0.4.140 Beta Need help?
A recreation of a real run. Fathom Analytics is a real company and not a customer. The counts are invented for the demo.
What comes back

One card, and two exports

It is built from the pages already crawled for this project, so every number traces back to a URL you own.

Entities
Every thing your site names

People, organisations, products, services, places, events and topics, each with the number of pages it appears on, plus a count by type.

Salience
What your site weighs most

A score per entity, weighted by where the name appears: structured data counts more than a title, and a title more than a heading. The score is compressed so one page repeating a name cannot dominate.

Relations
Three kinds, labeled separately

The connections your pages state, the ones that keep appearing on the same pages, and the ones whose names sit close in meaning. The card counts all three separately.

Exports
CSV and PDF, from the card

Entities with their type, aliases, page count, score and up to three source URLs each. Relations with their kind, source and confidence.

Two depths

Quick and Full

Both run against the crawl already on your machine, and both map the connections at the end. The difference is whether a model reads your body text.

Quick
What your pages declare

Reads the JSON-LD on your pages plus the names in your titles and headings. Seconds on most sites, no model involved, and nothing leaves your computer.

Use it for · The baseline, and checking that a schema fix landed.
Full
Adds an AI pass over your top pages

Pick the top 100, 250, 500 or 1,000 pages, ranked by Search Console clicks where it is connected. A model reads the body text and pulls out the things and connections you name in prose but never mark up. It runs on your local model, your OpenRouter key, or your monthly allowance on a managed plan.

Use it for · The fuller picture, once a quarter.
How to read it

How to read the card

A handful of numbers on the card each point at a different piece of work.

Three relations labeled, six hundred derivedOnly the labeled ones came from your own pages. That gap is the schema work
One brand, two entitiesA name appearing once as a product and once as an organization is a split worth fixing in your markup
Topics outnumbering everything elseYour headings name many subjects and your markup names almost no things
The highest salience entity is not your productWhatever sits on the most pages, in the most weighted positions, is what your site is about
An entity on a single pageA passing reference rather than a claim
Competitors inside your own graphNamed on your pages without a comparison you wrote
A person with no connection to the companyAuthor bylines on nine pages and nothing stating who they work for
The same labeled count after a schema changeRe-crawl and rebuild. If the number did not move, the markup did not land
How it works

Crawl once, then build it from chat

The pages are already on your computer from the site crawl, so the graph is built from your own site.

01
Crawl the site once

Site Monitoring crawls the project and keeps the pages locally. The graph runs on those pages, so it waits until one crawl has finished.

02
Build it from chat

Ask for an entity graph, pick it from the Tools menu, or use the button on a new chat. Same card either way: choose Quick or Full, then start.

03
Read the card, then export

Which type dominates, which entity carries the salience, and how many connections your pages state themselves. Take the CSV or PDF into the schema work, or ask Moose: he keeps the graph and reads it in any later chat.

Relations

Three kinds of connection

Every connection carries its kind, and the card counts them separately, so you can tell what your site states from what Moose inferred.

The three kinds, on one site
Fathom (organization)→ founder →Jack Ellis labeled Fathom Analytics→ appears with →Web Analytics 42 shared pages User Documentation→ related to →Fathom Analytics 0.61
Labeled
Straight from what your pages state

Author, publisher, brand, founder, works for, parent organization and a few more. Quick takes these from your JSON-LD and follows the @id references inside it. Full adds the ones a model finds stated in your prose. If no page says who founded the company, there is no founder relation.

Shared page
Things that keep turning up together

Entities that appear together on at least two pages, labeled "appears with" and carrying the number of pages they share. That is a pattern on your site, not a claim about the world.

Semantic
Names that sit close in meaning

A small embedding model runs on your computer, compares entity names, and keeps the three closest per entity above a similarity floor. Labeled "related to" and scored. This gives a site with no markup a usable graph.

Resolution
It merges, within a type

Case, punctuation and a trailing Inc, Ltd or GmbH fall away, so "NinjaOne, Inc." and "Ninjaone inc" become one entity. Two different types stay two entities, which is why a brand can appear as both a product and an organization.

Questions people ask

What is an entity graph, in plain terms?

A list of the things your site talks about, and the connections between them. Not keywords, and not pages. Seeing yours lets you decide whether it says what you meant.

Why are most of my relations shared-page or semantic?

Because those two are the ones Moose can work out on his own. Labeled relations come from your markup, plus anything the Full pass reads out of your prose, and on most sites the markup stops at the article template. So the labeled number starts low.

Do I need schema markup for this to work?

No. Without it you still get entities from your titles and headings, and connections from shared pages and name similarity. What you will not have is a labeled relation.

What does the Full pass cost?

Nothing beyond time on a local model. On a cloud model it spends your OpenRouter key, or your monthly allowance if you are on a paid plan. You choose how many pages it reads: 100, 250, 500 or 1,000. Quick needs no model at all and is free on every plan.

What do I need before I can build one?

A project with a website, and one site crawl that finished. The graph reads pages already stored on your machine, so if no crawl has run the card sends you to Site Monitoring first.

Can Moose use the graph after he builds it?

Yes. The graph stays with the project, and Moose can read it in any later chat. Ask which internal links to add or which schema gap to close first, and he answers from the graph. He keeps what your pages state separate from what he inferred. If the project has no graph yet, he offers to build one.

How is this different from a coverage check?

Coverage answers whether you have written about a topic. The graph answers what your site says you are.

How big does the graph get?

The card shows the true totals. The table and the exports carry up to 2,000 entities and 2,000 relations. If the AI pass was skipped, stopped or failed, the card says so.

More things to ask Moose

All use cases
Built on your machine

Crawl your site once,
then build the graph.

Download Hi, Moose, crawl your site once, and build the graph in seconds. Quick runs on the free plan.