We often take reading large documents as a tedious task and wonder if there exists a tool which provides us the crux of a large document. Imagine a research paper of 100 pages which consists of the information about some archaeological study. A student or a reviewer who wants to summarize such hundereds of research papers will have a hard time reading each paper word by word and then summarizing it. This kind of scenario requires a tool which summarizes important information from such huge text documents. This tool is made on this idea using Natural language processing algorithms along with a sentence scoring technique which scores sentences and gives them a rank according to the information provided in those. Sequential ranking helps to summarize a big text document and solves the overall problem of reducing the reading time by 70%.