Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: A framework for improving data set in an enterprise system for machine learning is provided. In accordance with one aspect, user input of a project update is provided by a user to an enterprise system. A record of the project update is created in the enterprise system based on the user input. The project update provided by the user into the enterprise system is analyzed using a gamification technique. The analysis includes quantifying the user's input of the project update to the enterprise system by assigning points to the user based on the project update provided to the enterprise system. The assigned points are displayed to the user on a user interface of a user device to enable friendly competition with other users which encourages more detailed and frequent project updates to the enterprise system by the user.

Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: A framework for improving data set in an enterprise system for machine learning is provided. In accordance with one aspect, user input of a project update is provided by a user to an enterprise system. A record of the project update is created in the enterprise system based on the user input. The project update provided by the user into the enterprise system is analyzed using a gamification technique. The analysis includes quantifying the user's input of the project update to the enterprise system by assigning points to the user based on the project update provided to the enterprise system. The assigned points are displayed to the user on a user interface of a user device to enable friendly competition with other users which encourages more detailed and frequent project updates to the enterprise system by the user.

Abstract: A framework for pre-sales marketing professionals who perform engagements, such as business-to-business engagements. Embodiments of the claimed invention optimize early activities in the sales cycle. For each prospective engagement, the embodiments generate a sales kit that assists the salesperson in getting through the “beauty contest” phase of enterprise solutions sales, in which multiple vendors compete for a prospect's business. Embodiments also function as a repository for product teams to showcase products to the company's salespeople. In this way, product teams are enabled to engage salespeople to market their offerings, and salespeople are enabled to quickly prepare for initial meetings with sales prospects.

Abstract: Disclosed herein are technologies for implementing an automated multimedia narrative—presentation to one or more users. In some implementations, the user selects and views an annual presentation report from a presented listing of digital multimedia narratives. Contents of the annual presentation report may be derived from stored information in the database and the derived contents are subsequently mapped to a humanlike—animation for delivery to the one or more users.

Abstract: Described herein is a framework for an integrated shopping assistance. In accordance with one aspect, the framework may detect a customer in an establishment. The framework may detect the customer by determining location proximity data of one or more detected customer-registered devices in an establishment. The framework may further perform, based on one or more data sources, image recognition of a captured image of a customer. Information associated to the customer may be retrieved from the one or more data sources. Real-time analytics may further be performed based at least in part on the location proximity data and the retrieved customer information. The framework may present, via a client device, a notification based on the location proximity data, a verification of the customer, the associated customer information, and results of the analytics.

Abstract: Described herein is a framework to facilitate adaptive transportation. In accordance with one aspect of the framework, sensor data from a user device is monitored to detect movement of a user during a trip to a venue of an activity. In response to detecting movement of the user, trip information is acquired via the user device. Such trip information may be streamed to a populace load balancer, a forecasting system, a transport analytics system or a combination thereof.

Abstract: Described herein is a technology for facilitating policy management. In accordance with one aspect, the technology includes, but is not limited to, gathering of personal data related to users, and determining policy topics that are relevant to the specific users based on their personal profile and other criteria as defined by the users. Policy updates, including new policies or changes to the existing ones, which are most relevant to the users may further be provided in a systematic way.

Abstract: Described herein is a descriptive framework to facilitate healthcare visit management. In accordance with one aspect, information of an appointment scheduled with a healthcare provider is received. A user's real-time location is monitored and the user's real-time location is used to facilitate a visit to fulfill the appointment. If waiting time of the user during the visit is estimated to be more than a predetermined threshold value, one or more recommendations may be presented via a user device to recommend relevant services, goods or entertainment options to the user.