05 / Diagnostic engine

Authority Graph turns a messy web presence into a build map.

The graph is the working layer behind an Authority Read: evidence, gaps, trust signals, AI visibility, and next actions mapped into one inspectable system before we recommend what to build.

Read the case Open anonymous sample

Proof surface

A read becomes easier to trust when the evidence is visible.

authorityread.com/authority-map

Anonymous Authority Map sample showing connected evidence, gap, risk, and opportunity nodes

Draggable anonymous sample Open sample map

Case spine

A stronger read starts with a better map.

Most web-presence work jumps straight from opinion to page changes. The graph gives the read a working model first: what proof exists, what is missing, which signals are public, and where the first build should land.

The situation

Expert-led businesses often have proof scattered across bios, articles, talks, pages, forms, referrals, and private context. Buyers and AI cannot use what they cannot find or explain.

The approach

We model the business as connected evidence: positioning, proof, web presence, AI visibility, conversion, operations, risk, and opportunity. Every node needs a source, status, and next action.

The build

The prototype uses structured client JSON and React Flow to render a constellation of pillars, evidence, gaps, and opportunities. Filters separate verified proof from inferred work.

The proof

The graph turns a read into an accountable plan: here is the evidence we found, here is what is inferred, here is what needs approval, and here is the first build that should move.

Start here

Wondering where your own buyers slip away?

An Authority Read maps the visibility and conversion leaks in your web presence, then names the first thing to build.

Start with an Authority Read

What it demonstrates

Diagnosis, proof discipline, and build priority in one tool.

The public map is a sample surface, not private client data. The production promise is the method: source-grounded reads that become prioritized builds.

Evidence

Source-backed nodes

Each signal is labeled as verified, planned, inferred, or not started, so the read does not blur proof with assumption.

Clarity

Gap scoring

The model separates positioning, proof, AI visibility, conversion, operations, risk, and opportunity before choosing the first build.

Action

Prioritized next steps

Nodes carry next actions, which makes the output useful for build planning instead of a static audit artifact.

Visibility

Buyer and AI readability

The graph makes it easier to see which public signals explain the business clearly and which ones need stronger packaging.

Governance

Approval boundaries

Private, inferred, or sensitive claims stay labeled until the owner approves what should become public proof.

Reuse

Repeatable read model

The same structure can support consultants, clinicians, speakers, nonprofits, and founder-led service businesses.

Proof standard

The graph distinguishes evidence from inference.

Authority Graph is not presented as a public client-result metric. It is an internal diagnostic engine and proof-planning tool used to make reads more specific, honest, and buildable.

The sample data intentionally labels inferred, planned, verified, and unverified items so the next build can be approved from evidence instead of vibes.

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Start here

Need a clearer map of what buyers and AI can actually understand?

The Authority Read maps the visible path, names the gaps, and turns the first priority into a practical build plan.

Start with an Authority Read Book a strategy call