An observational study of the visibility of Bangkok hospitals and clinics across ChatGPT, Gemini, Perplexity and Meta AI. The ranking describes citations observed across 83 patient queries at the collection date; it does not measure quality of care, safety or medical outcomes.
Four patterns emerge from 83 patient queries across four engines. They describe this measurement and should be tracked over time before being interpreted as durable market trends.
The KAIS Visibility Score is a relative visibility index within this panel, weighted by citation rank and multi-engine coverage and then normalised to the leader. It is not a probability of recommendation, market share or measure of medical quality.
The KVS formula explicitly rewards multi-engine coverage. In this measurement, 17 of 47 providers are cited by all four engines; the others show visibility concentrated in fewer systems.
Notable blind spot:
The observed hierarchy varies substantially by category. Large hospitals appear more often on some general queries, while several specialist clinics score better on targeted procedures.
Limitations. This is an observational study of engine outputs at a specific point in time. It does not establish that a particular page, link or source causes a citation, and it is not a medical recommendation.
KAIS measures AI-search visibility, the sources used by engines, competitor gaps and information risks for healthcare organisations. The engine panel is adapted to the target market and defined before the engagement. No citation or ranking is guaranteed.
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