  We define a symmetric monoidal category modelling fuzzy concepts and fuzzy
conceptual reasoning within G\"ardenfors' framework of conceptual (convex)
spaces. We propose log-concave functions as models of fuzzy concepts, showing
that these are the most general choice satisfying a criterion due to
G\"ardenfors and which are well-behaved compositionally. We then generalise
these to define the category of log-concave probabilistic channels between
convex spaces, which allows one to model fuzzy reasoning with noisy inputs, and
provides a novel example of a Markov category.
