I have read and watched a MAXQDA Tailwind webinar. I wanted to learn more! Stefan Radiker spoke at MAXQDA Days 2025 about “MAXQDA Tailwind: AI-driven Analysis for Qualitative Data.” Tailwind, Radiker explained, can summarize documents, identify themes, and soon chat with documents! Radiker used inaugural address speeches to create a project. Radiker noted that the name of the file and description are important for AI analyses. Tailwind creates a summary for every uploaded file. The summary is chronological order, and the references link to the part of the text mentioned. Next, Tailwind can suggest topics by analyzing all documents. Tailwind suggests a topic and provides a description. You can find topics automatically or add topics manually with Tailwind! The summary tables are a great way to compare where topics appear in different documents. Radiker shared how the web-based tool shares data with the AI model. At the moment, a maximum of twenty documents can be analyzed in Tailwind. Analysis of texts in different languages is possible. The summary display system in matrix format can be used for a variety of applications and analyses. I want to try to use Tailwind!
