As the use of multiscale and multiphysics models spreads out, the need to use stochastic models increases. However the numerical costs associated with the resolution of such models is usually much larger than that of their deterministic counterpart. We present here a method, set in the Arlequin framework, to couple a probabilistic model with a deterministic one, therefore introducing randomness only where necessary to improve the reliability of our quantities of interest.