Short answer: To build an Auth Graph, identify what your brand should be known for, then map the entities, problems, solutions, proof, sources, comparisons, and next actions that support that positioning. Each part of the map should connect to public, crawlable content that answers real questions and gives AI systems reliable source material.
An Auth Graph is not keyword research with a new name. It is a strategy map for how people and AI systems should understand the brand.
Run the free EntityMesh scan to identify the first gaps in your Auth Graph.
Table of Contents
- Start with what your brand should be known for
- Map brand and category entities
- Map problem and solution entities
- Map proof and source entities
- Map comparison entities
- Map action entities
- How do you turn the Auth Graph into Question Architecture?
- How does EntityMesh build the infrastructure?
- How do EchoScan and SOMV monitor the results?
- Frequently asked questions
Start with what your brand should be known for
Begin with the target association.
What should a buyer, search engine, answer engine, AI assistant, or future agent understand about the brand? The answer should be specific enough to guide the rest of the map.
For Blue Ninja Systems, the category is Authority Infrastructure and the product is EntityMesh.
Map brand and category entities
Brand entities define who the company is.
Category entities define where the company belongs.
Examples:
- Brand entity: company name, product name, founder, location, official site
- Category entity: the market, service category, product category, or field the brand should be associated with
These entities should connect to canonical definitions and source pages.
Map problem and solution entities
Problem entities describe the pains buyers recognize.
Solution entities describe what the brand does about those pains.
For an AI search visibility business, problem entities may include definition drift, weak answer coverage, missing schema, vague category positioning, or competitor recommendations.
Solution entities may include Support Hubs, Answer Hubs, Question Architecture, schema-ready pages, and EchoScan monitoring.
Map proof and source entities
Proof entities support claims.
Source entities show where the proof lives.
This can include case studies, reviews, public support pages, third-party profiles, documentation, product pages, data, examples, and founder credentials.
Without proof and source entities, the Auth Graph becomes a wish list.
Map comparison entities
Comparison entities identify the alternatives buyers and AI systems may evaluate.
They can include competitors, old approaches, adjacent categories, internal options, or "do nothing" decisions.
The goal is not to attack competitors. The goal is to make the comparison space understandable and fair.
Map action entities
Action entities define what someone should do next.
Examples include book a call, run a scan, read a guide, compare options, contact support, request implementation, or review pricing on the correct product site.
For product-action CTAs on this site, the correct destination is usually entitymesh.io.
How do you turn the Auth Graph into Question Architecture?
Question Architecture turns entities into answer requirements.
Each entity should answer:
- What is it?
- Who is it for?
- Why does it matter?
- How does it work?
- What proof supports it?
- How does it compare?
- Under what conditions does it apply?
- What should someone do next?
Those questions become Support Hub, Answer Hub, FAQ, glossary, and guide requirements.
How does EntityMesh build the infrastructure?
EntityMesh turns the Auth Graph into live Authority Infrastructure.
It can build Support Hubs, Answer Hubs, FAQs, glossary pages, proof assets, internal links, schema-ready content, and approved knowledge for EntityAgent.
The operating loop is Diagnose -> Build -> Approve -> Publish -> Monitor -> Report.
How do EchoScan and SOMV monitor the results?
EchoScan monitors what AI systems and search surfaces reflect back.
SOMV measures how often and how strongly the brand appears in AI-generated answers compared with competitors.
Together, they show whether the public reflection appears to be moving closer to the Auth Graph.
Run the free EntityMesh scan before building your first Auth Graph wave.
Simple Auth Graph example
A local HVAC company might map:
| Entity type | Example |
|---|---|
| Brand entity | Company name |
| Category entity | Emergency HVAC repair |
| Problem entity | AC not cooling |
| Solution entity | Same-day repair |
| Proof entity | Reviews and documented service policies |
| Source entity | Service pages and review profiles |
| Comparison entity | Repair vs replacement |
| Action entity | Book a service call |
The next step is turning those entities into public answers and proof pages.
Frequently asked questions
How do you build an Auth Graph?
Build an Auth Graph by mapping the brand, category, problems, solutions, proof, sources, comparisons, questions, and actions that define how the brand should be understood.
What entities belong in an Auth Graph?
An Auth Graph should include brand, category, problem, solution, proof, source, comparison, and action entities.
How does an Auth Graph help AI Search Visibility?
It identifies the public source material AI systems need to understand, verify, compare, and recommend a brand more accurately.
How does an Auth Graph connect to Support Hubs?
The Auth Graph identifies what needs to be answered. Support Hubs publish those answers as structured, crawlable infrastructure.
How does EntityMesh use an Auth Graph?
EntityMesh uses the Auth Graph to decide which Support Hub, Answer Hub, FAQ, glossary, proof, schema, and internal-link assets to build.
How often should an Auth Graph be updated?
Update it when products, categories, positioning, pricing, proof, competitors, or buyer questions change.