Cauliflower
Gianluca-Daniele Speranza is a co-founder and technological lead at Cauliflower, where responsibilities include addressing challenges related to the increasing volume of text data through an automated classification platform. Previously, Gianluca-Daniele served as a data scientist at ALD Automotive, focusing on the development and optimization of both traditional and machine learning-based statistical models for pricing applications, along with presenting insights to management and stakeholders. Earlier experience includes working as a data engineer and consultant at Musiol Oldigs Meyer MARKENDIENST GmbH, where contributions involved developing scalable data structuring processes, data pipelines, and business intelligence reporting. Gianluca-Daniele holds a Master’s degree in Politics & Public Administration with a focus on statistics from the University of Konstanz and a Bachelor’s degree in Political Science from Kiel University.
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Cauliflower
Cauliflower uses AI to deliver deep and intuitive insights from text. No manual training required. Cross-industry proven. 1. Gain a deeper understanding Out of the box, Cauliflower automatically identifies the most important topics, their associations, and the sentiment of your text data and visualises them in an interactive, intuitive dashboard. 2. Reduce mandatory setup work Cauliflower uses a unique unsupervised approach to save you time and money. No extensive setup is required on your part, no industry or case specific training data necessary. 3. Evaluate first, customise later Take advantage of the effortless setup and instead invest your time in making the analysis and visualisation work best for your business and your specific use case.