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Engineering intelligence, shipped.

Original research · Powered by Sourceable

The AI Visibility Index

A quarterly study of how AI assistants talk about brands — who gets mentioned, who gets misdescribed, and who gets cited — measured across four LLM engines from Sourceable’s continuous production monitoring. First edition: Q3 2026.

Get the first editionGet the first editionAbout SourceableAbout Sourceable

(01)What it measures

Four metrics, tracked as trends

Buying research is moving into AI assistants, and brands have no scoreboard for it. The Index publishes one — built on the measurement framework from our AI-visibility methodology, applied at industry scale.

01

Mention rate

Of the prompts a real buyer would ask in a category, the share in which a brand appears at all. The baseline metric — and for most brands, the humbling one.

02

Accuracy

When a brand is mentioned, are the facts right? Services, locations, pricing, and claims are scored against ground truth to quantify hallucination rates.

03

Sentiment & framing

How the answer positions the brand — leading option, niche alternative, or cautionary tale — tracked as a distribution, not a single verdict.

04

Citation share

When engines cite sources, whose pages get quoted. The metric that separates brands AI knows about from brands AI sends traffic to.

(02)Methodology

Built like an instrument, not a survey

01

Frozen prompt panels

Stratified panels of buyer-realistic prompts per industry — category discovery, comparisons, problem-first questions — frozen across editions so movement is signal, not rephrasing.

02

Four engines, continuously

Every prompt runs against ChatGPT, Claude, Perplexity, and Gemini through Sourceable’s production monitoring agents — the same infrastructure our customers use.

03

Sampled, not screenshotted

Model answers are probabilistic, so every prompt is sampled repeatedly per engine per period. Published numbers are aggregates with variance, never single runs.

04

Aggregated and anonymized

Published findings are industry-level aggregates. No customer’s individual monitoring data is disclosed — the Index reports the water, not the fish.

(03)First edition · Q3 2026

What the first report will answer

We publish findings only once the panels have enough samples to stand behind — aggregates with variance, methodology attached, and no cherry-picking. Until then, this page states what is coming rather than inventing numbers to fill it.

01Which industries surface brand recommendations most and least often
02How often engines state facts about companies that are simply wrong
03Per-engine differences: where Perplexity, Gemini, ChatGPT, and Claude disagree
04What cited pages have in common — the content shapes that win citations
05How AI answers shift after brands publish pricing and structured data

Want it when it lands?

Request the reportRequest the report