AI READINESS MONITORING

AIR tracks brand mentions, sentiment and Share-of-AI-Voice across all 5 major AI engines — OpenAI, Anthropic, Google, Perplexity and Mistral — with 10 model configurations and period-over-period trend deltas. Every aggregate carries its sample size and confidence band, so a 4-run snapshot is never presented as fact.

Built for executives receiving a shared AIR report, and agencies pitching monitoring to clients.

The receipt
MYTH
"3LA lacks trend analytics or Share-of-Voice."
FACT
5 engines, 10 model configurations, period-over-period deltas with confidence bands on every aggregate. This page is the proof.
METRIC HONESTY

Every number AIR reports ships with its sample size and confidence band — trustworthy numbers, not more numbers.

Live data unavailable — no number shown, to avoid presenting a placeholder as fact.

A single-digit run count is flagged automatically. AIR never rounds a snapshot into a claim.

WHAT AIR TRACKS

Four data points, tracked continuously across engines — not a one-time scan.

5 major AI engines · 10 model configs

OpenAI (ChatGPT / GPT-5.2), Anthropic (Claude Sonnet 4.5 & 4.6), Google (Gemini 2.5 / 3 / 3.5 Flash & 3.1 Pro), Perplexity (Sonar & Sonar Pro), Mistral Large — tracked in the same run, not sampled one at a time.

Period-over-period trend deltas

Share-of-AI-Voice movement week over week and month over month, not a single static score.

Sentiment per engine

Positive, neutral or negative framing, broken out per engine — engines disagree, and AIR shows it.

Sample-size transparency

Every aggregate carries n= and a confidence band, so low-volume snapshots are never presented as settled fact.

HOW IT WORKS

AIR runs the same brand query across engines on a fixed cadence, then aggregates with visible uncertainty.

  1. 01

    Define the query

    The brand + category prompt AIR runs across every engine.

  2. 02

    Run across 5 engines · 10 configs

    Same prompt, same window, all 5 AI engines queried in parallel across 10 model configurations.

  3. 03

    Score mentions & sentiment

    Each response is parsed for presence, sentiment and citation.

  4. 04

    Publish with confidence bands

    Aggregates ship with n= and a confidence band, never a bare number.

METHODOLOGY

AIR applies the same standard to 3LA as it does to your brand — nothing is hidden.

Confidence bands are derived from run count. A 4-run snapshot yields a wide band; a 40-run snapshot narrows it — the band is shown, not hidden.

This page's LayerScore
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Score published once this page audits at ≥ 90.

See your brand's Share-of-AI-Voice

Run a free AIR sample and see the confidence band before you see the score.

Measure change, not a single answer

AI Readiness Monitoring follows brand mentions, citations and sentiment across repeated model runs. Compare the same prompt set and model configuration over time before treating a movement as a trend. A change in the questions or engines is a change in the experiment, not necessarily a change in your visibility.

Keep the evidence beside the score

Use the sample size, confidence band and underlying answers to judge each result. Brand presence, a link to your website and a positive description are separate outcomes. AIR helps teams identify which engine needs attention without turning a small sample into a market-wide claim.

Frequently Asked Questions

What does AIR monitor?

Brand mentions, sentiment and Share-of-AI-Voice across OpenAI, Anthropic, Google, Perplexity and Mistral with period-over-period trend deltas.

How often does AIR run?

Configurable schedule — typically weekly. Same prompts across all engines in the same session.

What is a confidence band?

Shows how much a number could vary given the sample size. AIR always displays the band so you know the precision.

What is Share-of-AI-Voice?

How often your brand is cited relative to competitors for the same prompts. The AI equivalent of Share-of-Voice.

Can I track competitors?

Yes. AIR probes the same prompts for your brand and competitors side by side.