Narrative Integrity for AI

The gap

Where most AI brand monitoring stops.

The current generation of AI brand tools — what's now being called GEO or AEO — counts mentions, citations, and sentiment averages. Useful, but it's half the picture. None of them measure whether your message is actually landing intact, or what the AI still remembers from years ago.

What most AI tools tell you

Are you being mentioned?
Are you being cited?
What's the average sentiment?
How much share of voice across engines?

What Narrative Integrity adds

Is your message landing intact?
What is the AI still remembering — including frames you thought were behind you?
Where in the answer are you being placed?
Is the entity layer (Wikipedia, Wikidata, Knowledge Graph) clean enough for the AI to find you?

The methodology

Six pillars. One picture of how your brand performs inside AI.

Each pillar measures one specific dimension of how your brand shows up across the major AI engines — ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. The full audit reads them together.

PILLAR 1 Category Visibility

Are you showing up where buyers ask?

Maps your category's prompt universe across consumer, journalist, and institutional audiences. Surfaces where you're absent on questions you should own.

PILLAR 2 Brand Legibility

Can the model find you cleanly?

Audits the entity layer: Wikipedia, Wikidata, schema markup, Google's Knowledge Graph, AI crawler access. The foundation everything else depends on.

PILLAR 3 Source Authority

Where does the model trust you?

Tracks the third-party sources the AI cites for your brand: earned media, Reddit, customer reviews, YouTube. Identifies which channels are pulling weight and which are leaking authority.

PILLAR 4 Message Pull-Through

Is the story landing intact?

Compares the brand positioning you have invested in against what the AI actually says about you. Surfaces hijacked frames, drift, and competitor narratives that have leaked into your story.

PILLAR 5 Share of Model

Are you in the answer, or just the conversation?

Measures both how often you appear AND where in the answer you land. Top-of-list, mid-pack, or footnoted matters more than raw mention count.

PILLAR 6 Reputation Memory

What is the AI still remembering?

Surfaces the old crisis frames, calcified narratives, and outdated facts the AI still serves on demand. The frames you thought were behind you, that aren't.

Inside a Narrative Integrity audit

What you actually receive.

Every engagement produces a single diagnostic view: an overall performance read, a per-engine breakdown across the six pillars, and the cross-pillar findings most tools cant surface. The deliverable below is illustrative — the real version is scoped to your brand, your category, and the prompts your buyers actually ask.

Overall Performance

62

At Risk

Vacuum Exposed At Risk Solid Leading

Foundation is at the cap line. Pull-Through is leaking across all five engines. Two load-bearing cross-pillar findings.

Pillar performance × AI engine

	ChatGPT	Claude	Perplexity	Gemini	AI Overviews
P1 Category Visibility	68	62	66	60	64
P2 Brand Legibility	65	63	62	63	62
P3 Source Authority	72	70	71	68	70
P4 Message Pull-Through	52	55	57	54	58
P5 Share of Model	63	60	59	62	61
P6 Reputation Memory	38	42	39	40	39

Headline cross-pillar finding

"A competitor's product launch frame is being used to grade your brand inside ChatGPT."

Surfaced by Pillar 4 (Message Pull-Through), reinforced in Pillar 6 (Reputation Memory). The kind of insight no volume tool catches — only visible when the methodology reads pillars together.

DELIVERABLE 1

The Scorecard

A single diagnostic view of how your brand performs across the six pillars and the major AI engines. Banded so you know where you sit at a glance.

DELIVERABLE 2

Cross-Pillar Findings

The insights that only show up when pillars are read together. Hijacked frames, calcified narratives, the gaps a single-axis tool will always miss.

DELIVERABLE 3

Prioritized Actions

A sequenced remediation list — what to fix first, with effort sized (S/M/L). Built to be handed straight to your team or agency.

Illustrative example. Real audits are scoped to your brand, your category, and the prompts your buyers actually ask.

Find out where AI is shaping how customers see your brand — and where the gaps are putting you at risk.

Engagements are scoped to fit. A single diagnostic audit, a quarterly check-in cadence, or an embedded methodology partnership for in-house teams.