We present a deep neural framework that allows users to create surfaces from a stream of sparse 3D sketch strokes. Our network consists of a global surface estimation module followed by a local surface refinement. This facilitates in the incremental prediction of surfaces. Thus, our proposed method works with 3D sketch strokes and estimate a surface interactively in real time. We compare the proposed method with various state-of-the-art methods and show its efficacy for surface fitting. Further, we integrate our method into an existing Blender based 3D content creation pipeline to show its usefulness in 3D modelling.