Abstract: A method of self-learning actions for an automated co-browse session according to an embodiment include initiating an interaction between a user and a chat bot, determining a user intent of the user based on the interaction between the user and the chat bot, routing the interaction to a human contact center agent for a co-browse session between the user and the human contact center agent, storing a plurality of actions performed by the human contact center agent during the co-browse session to a data store, and performing machine learning to determine an optimal solution for resolving the user intent based on an analysis of the plurality of actions performed by the human contact center agent during the co-browse session.

Abstract: A method of asynchronously restoring an incomplete co-browse session according to an embodiment includes initiating an interaction between a user and a chat bot, determining whether data indicative of an incomplete co-browse session is stored in association with a user in response to initiating the interaction between the user and the chat bot, retrieving an intent configuration file associated with the incomplete co-browse session, wherein the intent configuration file defines a plurality of actions to be executed by the chat bot to resolve a user intent of the interaction between the user and the chat bot, and performing, via the chat bot and during a resumed co-browse session with the user, one or more actions of the plurality of actions defined by the intent configuration file that were not previously performed during the incomplete co-browse session.

Abstract: A system and method are presented for providing a contextual summary of an interaction between a first party and a second party over a media channel in an interaction transfer to a third party. A request is received to transfer an interaction to the third party, the request being triggered from the interaction. A text transcript of the interaction is obtained. The text transcript is processed to obtain the contextual summary and metadata, which is provided to the third party for handling the interaction with the interaction transfer. The contextual summary is provided by a contextual summarizer, which comprises a custom plurality of application programming interfaces (APIs). The plurality of APIs comprises at least one of: a text summarizer API, a churn predictor API, a sentiment analysis API, a next best action API, and an interaction reference detector API.

Abstract: A system and method are presented for providing a contextual summary of an interaction between a first party and a second party over a media channel in an interaction transfer to a third party. A request is received to transfer an interaction to the third party, the request being triggered from the interaction. A text transcript of the interaction is obtained. The text transcript is processed to obtain the contextual summary and metadata, which is provided to the third party for handling the interaction with the interaction transfer. The contextual summary is provided by a contextual summarizer, which comprises a custom plurality of application programming interfaces (APIs). The plurality of APIs comprises at least one of: a text summarizer API, a churn predictor API, a sentiment analysis API, a next best action API, and an interaction reference detector API.

Abstract: A system and method are presented for omni-channel notification and selection. A first party selects a first channel from a plurality of channels based on an estimated wait time for interaction with another party in a contact center or enterprise setting. The plurality of channels may comprise any means of interaction, such as chat, phone call, SMS, video, etc. While waiting in queue for the preferred first channel, the first party is presented with estimated wait times, which are dynamically updated, for other channels. Based on the first party's preferences and the presented estimated wait times for the other channels, the first party may elect to change interaction channels from the first channel to a second channel. The first party may then be moved to a different queue corresponding to the second interaction channel.