Correct representation of tidal processes in regional ocean models is contingent on the accurate specification of open boundary conditions. This paper describes a new inverse scheme for the assimilation of observational data into a depth-integrated spectral shallow water tidal model and the numerical implementation of this scheme into a stand-alone computational system for regional tidal prediction. A novel aspect is a specific implementation of the inverse which does not require an adjoint model. An optimization is carried out in the open boundary condition space rather than in the observational space or model state space. Our approach reflects the specifics of regional tidal modeling applications in which open boundary conditions (OBCs) typically constitute a significant source of uncertainty. Regional tidal models rely predominantly on global tidal estimates for open boundary conditions. As the resolution of global tidal models is insufficient to fully resolve regional topographic and coastal features, the a priori OBC estimates potentially contain an error. It is, therefore, desirable to correct these OBCs by finding an inverse OBC estimate that is fitted to the regional observations, in accord with the regional dynamics and respective error estimates. The data assimilation strategy presented in this paper provides a consistent and practical estimation scheme for littoral ocean science and applications where tidal effects are significant. Illustrations of our methodological and computational results are presented in the area of Dabob Bay and Hood Canal, WA, which is a region connected to the open Pacific ocean through a series of inland waterways and complex shorelines and bathymetry.