Getting AI/ML innovation out of the lab and into production means operationalising and scaling complex pipelines, and ensuring that the resulting signals are pushed into operational workflows where they can be actioned. We will briefly introduce Teradata’s extensive AI/ML capabilities and provide examples of how customers leverage them. We will also discuss Agentic AI, what it means for the data platform - and how Teradata’s industry-leading vector store is enabling customers to deploy scalable RAG applications.

Organisations are racing to adopt AI/ML solutions. But AI/ML solutions are only as trustworthy as the data used to train them, and are only impactful where we can deploy and operationalise them at scale. In this session we will discuss proven approaches to improving quality, reducing time-to-market for new analytics, and improving Data Scientist productivity, whilst also addressing concerns about ethics, compliance and data leakage.