Abstract: A method for policy-based analytics includes retrieving, from a graph database, first data representing a first entity in a computing environment, a second entity in the computing environment, and an event associated with the first entity and the second entity; predicting, according to a risk indicator model, a risk associated with the first entity based at least in part on the event; and updating the graph database to include second data representing the risk and a risk indicator. The first and second entities are stored as properties of a first vertex and a second vertex, respectively, and the event is stored as a property of an edge between the first vertex and the second vertex. The risk indicator is stored as a property of a third vertex. The risk is stored as a property of an edge between the first vertex and the third vertex.

Abstract: A platform comprising storage; a plurality of APIs; a plurality of resources; and one or more servers, the servers configured to enable a plurality of partners to build and manage a mobile ordering and payment facilitation application comprising a front end application and a back end application, the front end application configured to enable customers of each partner to browse products, purchase, view purchase history, set up product favorites, receive direct marketing, and wherein the back end application allows the partner to fulfill orders, track orders, manage inventory and push direct marketing to customers.

Abstract: A system comprising: at least one hardware processor; and one or more software modules that are configured to, when executed by the at least one hardware processor, receive a virtual rendering option; receive an image scan of a target area, generate a retail overlay comprising at least one virtual shelf with at least one product on a display; and once the overlay is fully rendered with the at least one product, receive a user interaction; and provide content in response to the received interaction.

Abstract: A method for policy-based analytics includes retrieving, from a graph database, first data representing a first entity in a computing environment, a second entity in the computing environment, and an event associated with the first entity and the second entity; predicting, according to a risk indicator model, a risk associated with the first entity based at least in part on the event; and updating the graph database to include second data representing the risk and a risk indicator. The first and second entities are stored as properties of a first vertex and a second vertex, respectively, and the event is stored as a property of an edge between the first vertex and the second vertex. The risk indicator is stored as a property of a third vertex. The risk is stored as a property of an edge between the first vertex and the third vertex.

Abstract: A platform comprising storage; a plurality of APIs; a plurality of resources; and one or more servers, the servers configured to enable a plurality of partners to build and manage a mobile ordering and payment facilitation application comprising a front end application and a back end application, the front end application configured to enable customers of each partner to browse products, purchase, view purchase history, set up product favorites, receive direct marketing, and wherein the back end application allows the partner to fulfill orders, track orders, manage inventory and push direct marketing to customers.