Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product that is likely to be of interest to the user is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application for the user is determined by the remote learning engine based on the accessed usage data, the recommended voice bundle application being a voice application that, when executed by the telephonic device, results in a simulated multi-step spoken conversation between the telephonic device and the user to enable the user to receive the identified service or the identified product. A recommendation associated with the recommended voice bundle application is transmitted from the remote learning engine to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications.

Abstract: A graphical user interface (GUI) on a display of an electronic device visually presents to a user a group of voice bundles that are available for use on the electronic device. Each voice bundle includes a software application for performing a call flow that includes a sequence of prompt instructions and grammar instructions executable to result in a simulated multi-step spoken interaction between the electronic device and the user. An input is received from the user entered through the GUI indicating a selection of a voice bundle from the group of voice bundles. In response to the input, a remote server is identified that stores the selected voice bundle. Network communications is established between the electronic device and the remote server. The selected voice bundle is located on the remote server. A copy of the selected voice bundle is downloaded from the remote server onto the electronic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented to the user through voice communications. One or more input parameters associated with the recommended voice bundle application is collected by the telephonic device. The user through voice communications has accepted the recommendation determining is determined. In response to determining that the user has accepted the recommendation, the one or more input parameters to the recommended voice bundle application are loaded by the telephonic device, and the recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product that is likely to be of interest to the user is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application for the user is determined by the remote learning engine based on the accessed usage data, the recommended voice bundle application being a voice application that, when executed by the telephonic device, results in a simulated multi-step spoken conversation between the telephonic device and the user to enable the user to receive the identified service or the identified product. A recommendation associated with the recommended voice bundle application is transmitted from the remote learning engine to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product that is likely to be of interest to the user is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application for the user is determined by the remote learning engine based on the accessed usage data, the recommended voice bundle application being a voice application that, when executed by the telephonic device, results in a simulated multi-step spoken conversation between the telephonic device and the user to enable the user to receive the identified service or the identified product. A recommendation associated with the recommended voice bundle application is transmitted from the remote learning engine to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented to the user through voice communications. One or more input parameters associated with the recommended voice bundle application is collected by the telephonic device. The user through voice communications has accepted the recommendation determining is determined. In response to determining that the user has accepted the recommendation, the one or more input parameters to the recommended voice bundle application are loaded by the telephonic device, and the recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A first service or a first product is identified by the remote learning engine based on the accessed usage data. A first recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the first recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications. A response from the user associated with the recommendation is received. In response to determining that the user has not accepted the recommendation, a second service or a second product is determined based on the received response. A second recommended voice bundle application is determined based on the second service. The second recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented to the user through voice communications. One or more input parameters associated with the recommended voice bundle application is collected by the telephonic device. The user through voice communications has accepted the recommendation determining is determined. In response to determining that the user has accepted the recommendation, the one or more input parameters to the recommended voice bundle application are loaded by the telephonic device, and the recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A first service or a first product is identified by the remote learning engine based on the accessed usage data. A first recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the first recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications. A response from the user associated with the recommendation is received. In response to determining that the user has not accepted the recommendation, a second service or a second product is determined based on the received response. A second recommended voice bundle application is determined based on the second service. The second recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application is determined by the remote learning engine. A recommendation associated with the recommended voice bundle application is transmitted to the telephonic device. The recommendation is presented to the user through voice communications. One or more input parameters associated with the recommended voice bundle application is collected by the telephonic device. The user through voice communications has accepted the recommendation determining is determined. In response to determining that the user has accepted the recommendation, the one or more input parameters to the recommended voice bundle application are loaded by the telephonic device, and the recommended voice bundle application is executed by the telephonic device.

Abstract: Usage data associated with a user of a telephonic device is accessed by a remote learning engine. A service or a product that is likely to be of interest to the user is identified by the remote learning engine based on the accessed usage data. A recommended voice bundle application for the user is determined by the remote learning engine based on the accessed usage data, the recommended voice bundle application being a voice application that, when executed by the telephonic device, results in a simulated multi-step spoken conversation between the telephonic device and the user to enable the user to receive the identified service or the identified product. A recommendation associated with the recommended voice bundle application is transmitted from the remote learning engine to the telephonic device. The recommendation is presented by the telephonic device to the user through voice communications.