LLM Visibility
LLM Visibility is a measure of how present and how favorably a brand is represented in the outputs of large language models across the queries where it should appear.
LLM Visibility is closely related to AI Visibility and often used interchangeably; the emphasis here is on the underlying models rather than the branded assistant products built on them. It covers whether a large language model reproduces accurate information about a brand, mentions it in relevant answers, and frames it in a fair light.
Two forces shape LLM Visibility: what a model absorbed during training, which reflects a brand's footprint across public text, and what it retrieves at answer time, which reflects current, indexable sources. Improving visibility means attending to both, since a brand can be well known to a model yet still absent from a specific grounded answer.
Brytic measures LLM Visibility by running a brand's prompts against several models, capturing each mention, its position, and its sentiment, and tracking how representation shifts as models, content, and sources change.