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The project aims at creating a web service, wherein you get restaurant suggestions based on parameters like your preferred cuisine, distance from current location, previous expenses footprint and the rating of the place. Following this, the user can visit/order from one of the suggested places and earn points, that in turn would benefit in terms of cost deduction in the overall order bill. The user gets to know of his/her calorie intake for the particular meal, which aids the process of future references. Further, the user gets extra points/credits if the he/she uploads an image of the bill and the bill no. gets matched, thus authenticating the usage of the service. Also, the user gets to rate the place as per the overall experience. For registration purpose using Twitter integration, the project uses VMs from IBMBluemix. Recognition and matching of bill no. against the bill image has been attained by the use of image processing and Optical Character Recognition tools by HP IDOL on demand. Also, attempts were made to incorporate the predictions feature using the predictive learning tool of IDOL on demand, but certain issues persisted with the functioning of the API. Further, geo location tracking features were incorporated and the Open Street Map tools were used for searching restaurants nearby the current location from the Clusterpoint Cloud along with the entire database and SQL queries running on the same.