Zero to production AI with integrated MLOps

About the webinar

AI teams can lose as much as 80% of their time to platform work, leaving only 20% for data science. This webinar shows how Canonical’s Managed Kubeflow on Microsoft Azure helps flip that ratio. If you’re building AI and struggling to accelerate – whether you’re breaking ground with a new AI-driven initiative, or running an established enterprise data science team – this webinar is for you.

The solution

Canonical’s Managed Kubeflow on Azure equips AI teams with a fully operational, open source MLOps platform in under half an hour – managed 24/7 by Canonical’s specialist operations engineering team, so you can focus on data science rather than running infrastructure.

Join our webinar to learn more about:

1. Onboarding and deployment: From zero to a working environment in under half an hour, and what that actually looks like step by step.

2. Technical demo: Running a real world predictive model pipeline for financial services, tracking an experiment, and serving a model end to end.

3. Solution overview: The three powerful, proven open source tools behind the platform – Kubeflow, MLflow, KServe – and how the managed service fits natively into your Azure account, billing, and support.

4. Real use cases for Canonical Managed Kubeflow in Azure: Fraud detection, LLM fine-tuning and distillation, automated pipelines for drug discovery, and more.

Presenters

• Massimiliano Gori – Product Manager, Enterprise applications, Canonical

• Rob Gibbon – Product Manager, AI and Analytics, Canonical

• Enrico Deusebio – Engineering Manager, AI and Analytics, Canonical