Integration is achieved by containerizing the trained model as a Docker image. The container runs on the customer's existing IT infrastructure and is accessed via an API interface. Existing systems retrieve the prediction as a service without having to modify their own architecture.

In this project, the AI model was integrated into the CarTV systems. Insurers and assessors use the prediction through the same interface they already know. The advantage of the container architecture: the model can be updated, scaled, and monitored independently of the rest of the application. No cloud dependency in production.