In this paper, we propose NightSight: a pipeline towards enhancement and de-blurring of low-light blur images. The challenges of low-light conditions and blurriness commonly arise in nighttime photography. Improvements in nighttime photography enhance visibility in low-light conditions, benefitting applications in computer vision like security surveillance, photography enhancement, astronomical phenomena, scientific research and many more. Current techniques find challenges in providing seamless solutions for simultaneous low-light image enhancement (LLIE) and image de-blurring. To address this, we propose a pipeline that incorporates an independent low-light image enhancement model and a de-blurring model. We present the results of the proposed pipeline on real-world datasets and compare its performance with state-of-the-art methods.