Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. In one embodiment, a method includes the operations of receiving, by one or more neutral network models on a cloud server, voice instructions captured by an interactive voice response (IVR) application on a mobile device, wherein the voice instructions are to update states of one or more tasks displayed in a voice interface of the IVR application; recognizing the voice instructions and constructing appropriate texts using the one or more trained neutral network models; presenting the texts to one or more voice interfaces provided by the IVR application for confirmation by a user; and storing the user confirmed texts to a repository on the cloud server.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. In one embodiment, a method includes the operations of receiving, by one or more neutral network models on a cloud server, voice instructions captured by an interactive voice response (IVR) application on a mobile device, wherein the voice instructions are to update states of one or more tasks displayed in a voice interface of the IVR application; recognizing the voice instructions and constructing appropriate texts using the one or more trained neutral network models; presenting the texts to one or more voice interfaces provided by the IVR application for confirmation by a user; and storing the user confirmed texts to a repository on the cloud server.

Abstract: The disclosure describes a method of training a prescriptive artificial intelligence agent to prescribe a next action for a sales opportunity. The method includes receiving a simulated task, and its attributes and associated actions at a training platform, which include the prescriptive agent to be trained and an environment. The method further includes receiving, at the environment, action information recommended by the prescriptive agent, the action information including a particular type of action and a state of the simulated task. The method further includes generating, by the environment, an indicator indicating whether the simulated task is associated with the type of action at the state of the simulated task, and determining a change in the state of the simulated task, the state change being a change in one or more attributes of the simulated task.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. In one embodiment, a method includes the operations of receiving, by one or more neutral network models on a cloud server, voice instructions captured by an interactive voice response (IVR) application on a mobile device, wherein the voice instructions are to update states of one or more tasks displayed in a voice interface of the IVR application; recognizing the voice instructions and constructing appropriate texts using the one or more trained neutral network models; presenting the texts to one or more voice interfaces provided by the IVR application for confirmation by a user; and storing the user confirmed texts to a repository on the cloud server.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. In one embodiment, a method includes the operations of receiving, by one or more neutral network models on a cloud server, voice instructions captured by an interactive voice response (IVR) application on a mobile device, wherein the voice instructions are to update states of one or more tasks displayed in a voice interface of the IVR application; recognizing the voice instructions and constructing appropriate texts using the one or more trained neutral network models; presenting the texts to one or more voice interfaces provided by the IVR application for confirmation by a user; and storing the user confirmed texts to a repository on the cloud server.

Abstract: Techniques for identifying similar companies based on profile data sets of the companies are provided. In one embodiment, a method comprises using a processing device to obtain a benchmark profile data set for a benchmark company and obtain a plurality of profile data sets, each of the plurality of profile data sets corresponding to a candidate company. The processing device may utilize a machine learning algorithm to determine the distance between each of the plurality of profile data sets and the benchmark profile data set and build profile graphs indicating the distance.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. The task database is in synchronization with a customer relationship management (CRM) system. The systems and methods described herein enable users to update the task database and enter information into the task database in a timely manner such that the task database can stay updated. The updated database can be used to construct a suggested task set at the beginning of a period of time to meet a preset target sales value for the end of the period of time.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. The task database is in synchronization with a customer relationship management (CRM) system. The systems and methods described herein enable users to update the task database and enter information into the task database in a timely manner such that the task database can stay updated. The updated database can be used to construct a suggested task set at the beginning of a period of time to meet a preset target sales value for the end of the period of time.

Abstract: Described herein are systems and methods for facilitating the information entry and task updates to a task database in a cloud server. The task database is in synchronization with a customer relationship management (CRM) system. The systems and methods described herein enable users to update the task database and enter information into the task database in a timely manner such that the task database can stay updated. The updated database can be used to construct a suggested task set at the beginning of a period of time to meet a preset target sales value for the end of the period of time. In one embodiment, a system includes a mobile application to capture contact information from a physical medium as an image, and to send the image to a cloud server, where a trained neural network model is to extract contact details and send the contact details back to the mobile application for editing and confirmation by a user.