Christopher Nuland demonstrates Red Hat OpenShift AI in the loose context of an insurance company processing claims combining generative AI for summarization and sentiment analysis with predictive AI for vehicle images all on a single AI platform. This demo provides a walkthrough of how to use OpenShift AI for training and experimentation, highlighting how to create data science projects, import data, load the Jupyter notebooks and then train the models. Christopher uses Mistral-7B for summarization and sentiment analysis. For image detection for the claim, the YOLO model is used and retrained with accident data.