An automated system can be devised to digitalize the present manual attendance system using face recognition models. The model can be deployed on micro-computers to detect the faces of students with great accuracy and simultaneously log their attendance. A ML-based handwriting recognition system can be used to automate the manual answer script correction process by text extraction from answer script, measure various similarities from summarized extracted text and to score the marks to the answer script to keyword-based summarization techniques. It can go a long way in eliminating human error and provide an unbiased result while also resulting in the timely delivery of scores to students.