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AI Narrative Intelligence

AI is where consumers decide what to buy.
Most brands have no idea what it's saying about them.

Every day, consumers ask AI about your brand and get an answer. You're not in the room. You don't know what it said. We find out — and tell you what it's costing you.

Get Your Free Scan → See the demo ↓
58%
Of consumers use AI before they buy ↗
3,400+
AI responses scored per brand audit
2
Revenue exposure pools measured — new buyers and at-risk existing customers
4
AI models audited — GPT-4o, Gemini, Claude, Perplexity
What We Measure

There are 200+ tools that tell you if you show up.
None of them tell you what happens next.

Showing up in AI and being chosen by AI are two completely different things. A brand can appear in 94% of category conversations and get recommended in 2.5% of them. The gap is what we measure — and it's driven by what the model says in the middle of the conversation, not just whether it knows your name.

Net Pull: the metric that predicts conversion
Sentiment measures how an AI talks about your brand. Net Pull measures what it does to purchase intent — they're not the same thing. A warm, positive response can still embed enough friction to lose the sale. Net Pull catches it. Sentiment doesn't.
Adversarial pressure testing
We run 13 types of stress prompts — ingredient concerns, health claims, bad press — and score where your narrative breaks. This is where most brands discover they have a problem.
Competitor displacement
Even when consumers ask about you specifically, AI volunteers alternatives. We map which competitors get planted, how often, and at which funnel stage they enter.
Purchase path efficiency
Most brands think their AI problem is awareness. It isn't. Path Efficiency = Discovery Rate × Evaluation Win Rate. We calculate what percentage of AI-assisted category journeys actually reach a recommendation for your brand — and identify exactly where the funnel collapses.
Narrative depth
How deeply are negative narratives embedded in training data? We measure whether concerns are surface-level or structurally baked in — the difference between a content fix and a long-term problem.
Factual accuracy verification
AI states false product claims with complete confidence — ingredients, certifications, dosages. Consumers act on them. We verify every factual assertion against ground truth so you know exactly what's being fabricated, and in which model.
Revenue exposure quantification
We translate AI narrative problems into dollar terms using a two-pool model: the fair share gap among new buyers who should be choosing you but aren't, and the switching risk among existing customers being nudged toward alternatives mid-conversation.
See It In Action

This is a real consumer conversation.
Your brand lost it before the third message.

Watch how AI introduces doubt, surfaces a competitor, and makes a recommendation — in a conversation your brand will never see.

Live narrative signalAI Signal
Funnel stage
—
Sentiment
—
−1.0 to +1.0
Competitor
—
mentions
Net Pull
—
−1.0 to +1.0
Rec. outcome
—
Brand A vs B
9:41
ChatGPT ⌄
Message
● Live narrative signal — Brand A
Sentiment
—
−1.0 to +1.0
Competitor
—
mentioned
Net Pull
—
−1.0 to +1.0
Rec. outcome
—
Brand A vs B
01 — Discovery
Brand A is introduced — but so are two competitors
The AI mentions Brand A first, then offers two cleaner alternatives. Sentiment is +0.6 — the AI sounds positive. Net Pull is only +0.2. The gap is friction already embedded in the framing. A sentiment-only tool calls this a win.
Sentiment
+0.6
Competitor mention
2×
Net Pull
+0.2
Rec. outcome
Neutral
02 — Evaluation
Caveats start — friction enters the conversation
The AI surfaces ingredient concerns without being pushed. Sentiment drops and Net Pull turns negative — the model is now introducing more doubt than motivation.
Sentiment
−0.1
Competitor mention
—
Net Pull
−0.1
Rec. outcome
Neutral
03 — Conversion lost
The AI picks a winner. It isn't Brand A.
Net Pull collapses to −0.8. Friction won. Brand A lost the sale inside a conversation it never knew was happening — and the brand that gets recommended here gets recommended again.
Sentiment
−0.7
Competitor mention
1×
Net Pull
−0.8
Rec. outcome
Lost to B
How We Work

Start free. Go as deep as the finding warrants.

Every engagement starts with a free scan — a real look at where your brand stands. What we find determines where to go next.

✦ Free Signal Scan
Get your baseline.

A fast read of how AI represents your brand right now — before a product launch, a campaign, or a board conversation about AI.

Net Pull score — motivation vs. friction in AI responses
Whether AI recommends you or steers toward a competitor
One model, one clear baseline
Get Your Free Scan →
Narrative
See what's driving it.

Which models are hurting you, which competitors AI is recommending in your place, and which consumer conversations are the source of the problem.

All three major AI platforms compared
Competitor displacement mapped by stage
Six consumer archetypes tested
Start with a free scan →
Deep
Know what to fix.

The full audit: adversarial pressure testing, financial exposure modeled in dollars, and a prioritized action plan — each lever ranked by estimated revenue recovery.

Stress tested across 13 adversarial scenarios
Revenue exposure quantified — two-pool model
Prioritized action plan with recovery estimates
Start with a free scan →
Custom
Your category, fully mapped.

Multiple brands, category-wide competitive intelligence, or ongoing monitoring. If the scope is unusual, we'll figure it out together.

Your model mix, your competitors
Quarterly monitoring retainer available
Category intelligence across multiple brands
Talk to us →
About

Built by two practitioners with deep roots in marketing science and competitive intelligence. We know what rigorous brand measurement looks like — and we built Tenor Narrative because nothing rigorous existed for AI.

01
Variance-validated methodology
Every category in our prompt set has been tested for statistical stability — calibrated run counts, held-constant scorer logic, and locked model versions. The numbers we report are repeatable, not anecdotal.
02
Four models, full funnel
GPT-4o, Gemini, Claude, and Perplexity — scored across Discovery and Evaluation. We measure where AI loses your customer and what the Path Efficiency number actually is, not just whether it knows your name.
03
Independent and rigorous
We don't sell AI tools. We don't manage your content. We don't optimize your prompts. Our only product is an accurate, defensible picture of where your brand stands — and what's actually worth fixing.
Get Your Free Scan →

Find out what AI is telling your customers before your competitor does.

We'll run your brand through the intelligence pipeline and send you a real snapshot — Net Pull score, competitor displacement, and your Path Efficiency baseline. No cost, no obligation.