From Prototype to Product – Scale your AI solution without losing control over complexity

Please note that the workshop will be in English. This is the second workshop in the series - you can sign up for 1, 2 or both workshops. 

A practical workshop that guides you from prototype to product readiness. Learn how early architectural choices impact scalability, explore common post‑prototype pitfalls like data drift and monitoring, and refine your prototype with real‑world constraints in mind. 

• Learn how to move from prototype to a real AI product that can run reliably in production and deliver consistent business value.
• Understand how to scale AI solutions responsibly, including infrastructure, governance, and integration with existing systems.
• Gain practical strategies to manage complexity and risks as your AI solution grows and is used by more people in the organization.

This workshop picks up where the prototype leaves off - and where reality usually begins. Participants will continue developing their prototype while exploring what it takes to move toward a real, usable product.

MLOps is introduced as a cautionary tale of everything that can go wrong after the prototype stage. We’ll discuss challenges like data drift, reproducibility, monitoring, and operational complexity - without diving deep into implementation details.

You’ll see how early architectural and tooling decisions affect scalability and maintainability. Participants will refine their prototypes with these constraints in mind.

By the end of the workshop, you’ll have a stronger prototype and a realistic understanding of the path from demo to deployment.