Angel Co., Ltd.

Other

Genesys Telecommunications Laboratories, Inc.

Jonathan Hotz

Michael Jerry Saylor

Ahmed Tewfik Bouzid

David James Rennyson

Ashwini Swaroop Reddy Dulam

Prasanna Sajeewa Naleen Perera

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. The user through voice communications has accepted the recommendation determining is determined by the telephonic device. In response to determining that the user has accepted the recommendation, the recommended voice bundle application on the telephonic device is executed by the telephonic device.

Conversation assistant

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.

Preloading contextual information for applications using a conversation assistant

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.

Dynamic adjustment of recommendations using a conversation assistant

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Reston, VA, United States of America

Jonathan Hotz