Case Study: Eidos-Montréal turns player feedback into actionable insights with Kili Technology

Eidos Montreal improves text annotation quality and speed with Kili Technology

Eidos-Montréal, a video game studio, needed to extract strategic insights from thousands of player reviews and articles but struggled to scale its data annotation process using open-source tools. The challenge was to train machine learning models on this unstructured text data efficiently while ensuring consistent, high-quality labeling. They turned to Kili Technology's data labeling platform to address these obstacles.

By implementing Kili Technology's platform, which featured consensus-based quality control and a professional labeling workforce, Eidos-Montréal significantly improved the speed, scalability, and quality of its annotation process. The solution enabled the team to build reliable machine learning models that now provide actionable insights, guiding marketing strategies and game development. Kili Technology empowered the studio to make confident, data-driven decisions across the organization.

Eidos Montreal