Clear Cited AI Visibility Index: share of model across five AI engines, nine B2B software categories

An open, pre-registered measurement of which products generative AI engines name and cite when buyers ask for software recommendations. Nine B2B software categories were measured on 2026-07-01 across five AI engines — ChatGPT (OpenAI), Perplexity, Claude (Anthropic), Gemini (Google) and Grok (xAI) — using a fixed protocol of 10 prompts × 10 runs per engine, yielding 500 AI answers per category. The dataset covers 4,497 AI answers and 34,801 citations across 90 ranked products. For each product we report share of model (the proportion of qualifying AI answers naming the brand), a 95% Wilson confidence interval on that share, appearance rate, citation rate, raw mention count and answer total. The accompanying JSON additionally carries per-engine breakdowns, full citation-source records, capture timestamps and model identifiers. Prompts and the brand universe were hashed and frozen before the run; the pre-registration hashes are included in each JSON record. Products cannot pay to appear or to rank. Google AI Overviews and Microsoft Copilot are treated as answer surfaces and measured separately. They are never summed into the five-engine share of model. **Categories:** AI observability tools · API platforms · CI/CD platforms · CRM software · databases · feature flag platforms · incident management platforms · product analytics platforms · vector databases. **Limitations.** A single measurement run captures one point in time; model versions change beneath the measurement, which is why every record is dated at capture. Ten prompts per category is a deliberate trade between coverage and cost, and does not span every phrasing a buyer might use. The confidence intervals describe sampling variation within this protocol; they do not account for model drift between runs.