With the rapid rise of AI, organisations are eager to adopt AI models into their workflows, yet model deployment remains complex, resource-intensive, and prone to security risks, making it difficult to experiment and iterate with. Enter Ramalama, an open-source tool that simplifies inferencing of AI models with the familiar approach of containers, while keeping everything local.

In this workshop, you’ll get an in-depth introduction to Ramalama, its flexibility with container engines, model registries and inference runtimes, how it abstracts underlying complexities, can help streamline your workflow, making AI model deployment a straightforward process.

Attendee Takeaways:
Understanding of Ramalama's role in integrating AI models with container technology.
Insights into the security and performance benefits of running AI models in isolated containers.
Practical knowledge on deploying and scaling AI workloads using Ramalama.