Our Team

Caleb Cooper is an AI practitioner who brings a practical, systems-oriented approach to workflow discovery, model evaluation, and responsible AI implementation. He focuses on understanding how people use information, where workflows break down, and how AI can be applied to improve research quality, operational efficiency, and decision support.

Caleb’s background includes hands-on experience evaluating large language models and supporting data quality workflows through organizations such as TELUS Digital, Outlier AI, and Snorkel AI. His work has included assessing model outputs against structured guidelines, testing instruction-following behavior, identifying failure patterns, and contributing to improvements in reasoning, relevance, safety, and alignment with user intent.

He is currently focused on mapping business workflows, tools, data needs, and implementation opportunities across consulting, advisory, marketing, HR, and operations functions. His approach emphasizes practical systems, human oversight, governance, and clear implementation pathways that help organizations move from experimentation to responsible AI adoption. Caleb is pursuing a Master of Science in Artificial Intelligence at Florida Atlantic University and has prior academic training in information management and biotechnology.