Thomson Reuters Labs

Our process often begins with user research and design thinking workshops to understand the human side of systems and to inform our thinking about what problems should be solved. Rapidly creating prototypes allows us to explore solutions, validate them through customer testing, and de-risk their further development. Through this process we build functional front-end interfaces and visualizations to support the understanding of our customers’ needs.

Our data scientists work closely and in a rigorous, systematic way with subject matter experts to determine how well our machine learning (ML) models are working and what level of performance is appropriate to the task being automated. They apply the latest developments in machine learning, including applications of deep learning, natural language processing (NLP), predictive modeling, classification, text generation, text summarization tasks, and more.

We enable the transition of design and research work into the hands of our segment partners, accelerating adoption of innovative solutions for our customers. Our engineering team works alongside our design and data science teams to execute the latest developments in software design. In addition to helping the company deploy machine learning solutions, our engineers prototype solutions utilizing decentralized ledger technologies, identity services, public cloud, and other emerging and fast evolving fields.