This work presents a model for the development of affective assistants based on the pillars of userstates and traits. Traits are defined as long-term qualities like personality, personal experiences; preferences, and demographics, while the user state comprises cognitive load, emotional states, andphysiological parameters. We discuss useful input values and the necessary developments for anadvancement of affective assistants with the example of an affective in-car voice assistant.