Shadow Deployment

A deployment strategy where a new AI model receives live production traffic in parallel with the existing model but does not serve predictions to end users, used for validation and comparison.

Running a new AI model alongside the current one, processing the same requests, but not actually using its results. This lets you compare performance risk-free before switching over.