In-Situ processing requires modifications to simulation code to host the visualization pipelines and provide access to the data. For researchers, this means additional effort without immediate discernible value, and hence resistance to invest in code changes. In this talk we propose our approach to this dilemma which we call Inshimtu, because it is an in-situ shim. Inshimtu is a hybrid in-situ co-processing approach that works with existing simulation output files, and thus does not require any changes to the simulation code. We are using burst buffer (BB) based on Cray DataWarp technology to speed up data transfers. The Inshimtu application reads the files from the BB nodes and performs the visual pipeline processing and analysis using the VTK toolkit (part of ParaView) and ParaView Catalyst. The visualization pipelines and scripts used with Inshimtu are exactly the same as those used by the fully simulation-embedded version of Catalyst. Inshimtu is thus a stepping stone from basic to complete in-situ visualization. Visualization pipelines will work for pure in-situ simulations when scientists do upgrade their simulation codes, thereby providing continuity and preserving investment in existing visualization pipelines. We will present our experiences, benchmarking results taking into account BB optimizations, and evidence for the feasibility of our Inshimtu framework using on ongoing climate simulation project. It is our hope that Insimtu will help to more easily convince domain scientists of the benefit of in-situ visualization approaches by providing them preliminary results without having to invest too much time and effort in the implementation of an actual in-situ approach.