It is so easy for people, now a days, to access information by the rapid development of online news, but the problem of information overload has created a lot of problems. User used different websites to search news related their interest, available time and location. EZ Bulletin is developed in order to provide a personalized and simple solution for providing accessible news. This proposed mobile app is collecting news from various online websites and organized into location based, latest and trending categories. Natural Language Processing (NLP) techniques are also used in order to generate summarized form of lengthy articles. With addition of text-to- speech feature, it allows the users to listen the summarized form of news instead of reading. This system supports the offline access, notifications, feedback, saved content, personalized news preference and user registration. Firebase is needed for data management and notifications, while technologies related to mobile applications are used in order to give an interactive interface. Testing is performed by integration, functional and unit testing. It has been as shown through documented test cases the successful operation of various important functions like registration of user, login with summarization of news. This proposed system is demonstrating how mobile technologies, NLP, artificial intelligence and web scraping could combine together in order to make news consumption more personalized, easier and faster.