AI Ops with DataBricks Part 2

Stop Experimenting. Start Delivering. Go from Proof-of-Concept to Production.

We continue with Part 2 of our AI Ops with Databricks series, where we explore how to move from AI experimentation to real, production-scale value.
In this session, Wynand Jordaan and Matthew Thomson will unpack the practical steps, architecture patterns, and operational best practices for delivering AI at scale using Databricks.
We’ll discuss:

• How AI Ops bridges the gap between data science and production systems
• Leveraging Databricks to operationalise machine learning workflows
• Building robust monitoring, observability, and governance for AI models
• Expert heuristics, tips, tricks and rules of thumb for building reliable agentic systems
• Real-world examples of accelerating AI delivery and reducing time-to-value

Whether you’re a data engineer, data scientist, or tech leader looking to scale AI impact, this session will give you actionable insights and a roadmap to production success.
Speakers:

• Wynand Jordaan – AI & Data Engineering Specialist, passionate about scaling intelligent systems in production.
• Matthew Thomson, PhD –Director for Architecture, Consulting and Enablement for UK&I at Databricks, focused on helping customers build and deploy Apache Spark and machine learning models at scale.

Join us to learn, share ideas, and connect with others shaping the future of AI operations.