An observational study of law-firm visibility in Paris and Lyon across Gemini, Meta AI and Perplexity. The results describe citations observed across 80 legal queries at the collection date; they do not measure legal quality, professional competence or case outcomes.
Six patterns emerge from 80 real-world legal queries across three engines. The panel contains 240 question × engine cells, each measured three times; 640 citations were recorded in the consolidated dataset used for the ranking.
The KAIS Visibility Score is a relative visibility index within this panel, weighted by citation rank and multi-engine coverage and then normalised to 100 per city. It is not a probability of recommendation, market share or assessment of legal quality.
The three engines name neither the same number of firms nor the same ones. A firm can be perfectly visible on Gemini and absent from Meta AI for the same question. Optimizing for a single engine caps your visibility.
The cost wall:
The hierarchy changes radically from one practice area to the next — and from one city to the other. The Reference Rate is the share of answers that name at least one firm in the area.
This view separates high-intent queries where one firm repeatedly leads, queries where leadership varies by engine, and queries where no firm is cited. It is designed to prioritise editorial and authority experiments; it does not describe reserved positions or guaranteed opportunities.
Fine per-query read: ranking of cited firms and their position on the Gemini + Meta AI text sub-panel (Perplexity remains included in the aggregate KVS). "Recurrent leadership" means a firm repeatedly appeared at the top of the observed sub-panel. "Fragmented" means leadership differs by engine. These labels are descriptive and may change over time.
Limitations. This is an observational study of engine outputs at a specific point in time. It does not establish that a particular page, source or action causes a citation and is neither a ranking of legal quality nor a recommendation of a law firm.
KAIS works with law firms that need to measure and strengthen their visibility in AI search, using a market-appropriate engine panel, archived measurements and a framework compatible with professional-conduct requirements. No position or citation is guaranteed.
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