risura

Corpus of analyses

Research on the AI trace of brands

Materials on how language models describe service and technology companies: which categories they choose, which neighbours they pull in, where the product function gets lost. Organised by type of shift and practical scenario.

13 plates · 3 directions · pt-PT, en

Direction I

Entity and category

The most visible signal, but poorly described: the model sees the company, catches part of its function, and shifts it into a neighbouring category. In Portuguese contexts, this is frequent.

Direction II

Language traces and neighbours

The brand’s surroundings in the text. The model reconstructs it from traces: words on the website, competitor descriptions, sector formulas that recur.

Direction III

Runs and the stability of errors

Closer to the method: the same prompts, different models, semantic trajectories that recur. The lab separates noise from a stable shift.

Every analysis begins with a model answer that sounds almost right.

Then the team looks at what, inside that “almost,” changes the brand entity.

About the method →