At the beginning of 2025, TVA launched Digital Talks, a series of meetings inviting designers and industry professionals to share their experiences. To document these conversations and preserve their insights, the team experimented with parametric and generative design, creating a data-driven poster for each speaker. In these visuals, data takes the form of a landscape, while colour gradients reflect the audience’s perception of the talk. In this process, words are transformed into data on two parallel levels. First, they represent the semantic content of the speech. Second, they act as triggers capable of generating a reaction in listeners. The superposition of these two dimensions defines the final composition. The first analysis is quantitative. Each word is treated as a data point whose frequency and association with other terms reveal recurring themes and conceptual connections. For this purpose, TVA developed a textual analysis tool based on the Claude algorithmic model. The tool processes talk transcriptions generated via Microsoft Teams, removing filler words and common spoken-language structures. The resulting network of nodes and connections highlights the density and relationships between key concepts. This network is interpreted as a landscape: each node becomes a mountain whose height and size correspond to the frequency of the word. Closely related concepts form mountain ranges, while more isolated ideas appear as standalone peaks. The second analysis is qualitative and focuses on audience perception. At the end of each talk, participants answer two questions about immediate impact and future intention. Each response is mapped to a colour, and the dominant answers define the background palette of the landscape, producing 16 possible combinations designed with accessibility and contrast in mind. In the final composition, the structure represents what was said, while colour expresses how it was perceived. Contextual details complete each unique, data-driven artifact, rooted in the shared experience of a specific moment.