Data & Models

Sessions focus on: 

• Scaling multi-agent and enterprise AI systems beyond pilots  

• Securing AI across the model, pipeline, and runtime  

• Managing data privacy, governance, and compliance at scale   

• Turning AI into measurable business impact, not just experimentation  

• Making cost vs performance trade-offs across infrastructure and models 

The track is structured across the full lifecycle: 

• Agentic systems and model architecture  

• Privacy, security, and governance  

• Infrastructure optimisation and scaling  

This reflects the reality that performance gains now come from the interaction between data, models, and infrastructure, not any one layer alone.