The objective of this thesis is to generate on-demand assistance in SEPIA project while taking into account the user's context. Currently, when a user requests assistance for a given application, our system provides the list of all available assistances. The assistances being created by application experts are not user tailored. In order to make relevant and intelligent on-demand assistance, we will explore two axis: context-aware assistance recommendation and assistance adaptation at runtime.