One example method of operation may include determining a call received from a calling party and intended for a subscriber device has an elevated likelihood of being a scam call, determining a percentage of calls over a current period of time being filtered as scam calls by a carrier server, when the percentage of calls being filtered as scam calls during the current period of time is above a call threshold percentage, retrieving call history information associated with a subscriber profile of the subscriber device, identifying one or more call patterns from the call history information of the subscriber profile corresponding to the received call, and determining whether to permit the received call based on the identified one or more call patterns.

Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for pairing in a contact center including ordering one or more contacts, ordering one or more agents, comparing a first difference in ordering between a first contact and a first agent in a first pair with a second difference in ordering between a second contact and a second agent in a second pair, and selecting the first pair or the second pair for connection based on the comparing, wherein the first contact and the second contact are different or the first agent and the second agent are different.

Methods and systems for routing multimedia traffic are described. A method may include receiving a communication originating from a user, transposing an alias transport network over one or more existing networks to route the communication, and routing the communication based on mapping rules.

Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for pairing in a contact center including ordering one or more contacts, ordering one or more agents, comparing a first difference in ordering between a first contact and a first agent in a first pair with a second difference in ordering between a second contact and a second agent in a second pair, and selecting the first pair or the second pair for connection based on the comparing, wherein the first contact and the second contact are different or the first agent and the second agent are different.

Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for pairing in a contact center including ordering one or more contacts, ordering one or more agents, comparing a first difference in ordering between a first contact and a first agent in a first pair with a second difference in ordering between a second contact and a second agent in a second pair, and selecting the first pair or the second pair for connection based on the comparing, wherein the first contact and the second contact are different or the first agent and the second agent are different.

Techniques for benchmarking pairing strategies in a contact center system are disclosed. In one embodiment, the techniques may be realized as a method for benchmarking pairing strategies in a contact center system comprising: determining for each contact of a plurality of contacts, an associated plurality of historical contact assignments; determining, for each contact, an associated outcome value; partitioning, for each contact, the associated plurality of historical assignments into a first associated subset assigned using a first pairing strategy and a second associated subset assigned using a second pairing strategy; determining, for each contact, a first portion of the associated outcome value attributable to the first associated subset and a second portion of the associated outcome value attributable to the second associated subset; and outputting a difference in performance between the first and second pairing strategies according to the first and second associated portions of the associated outcome value for each contact.

Techniques for benchmarking pairing strategies in a contact center system are disclosed. In one embodiment, the techniques may be realized as a method for benchmarking pairing strategies in a contact center system comprising: determining for each contact of a plurality of contacts, an associated plurality of historical contact assignments; determining, for each contact, an associated outcome value; partitioning, for each contact, the associated plurality of historical assignments into a first associated subset assigned using a first pairing strategy and a second associated subset assigned using a second pairing strategy; determining, for each contact, a first portion of the associated outcome value attributable to the first associated subset and a second portion of the associated outcome value attributable to the second associated subset; outputting a difference in performance between the first and second pairing strategies according to the first and second associated portions of the associated outcome value for each contact.

A system for transitioning a telephony or in-person servicing to an artificial intelligence (AI) chat session is disclosed. The system may receive a phone call from a user device associated with a user, and transmit a voice request for personally identifiable information associated with the user. The system may also receive and authenticate the requested personally identifiable information and, in response, generate an authentication token. The system may further receive a servicing intent from the user device, and generate a corresponding servicing intent token. Also, the system may generate an API call to an AI chatbot model, transmit the authentication token and the servicing intent token to the AI chatbot model, and map the servicing intent token to a stored servicing intent. Finally, the system may transmit a message to the user device via the AI chat session.

System, method, and various embodiments for providing a digital on-duty assistant are described herein. An embodiment operates by receiving a support request from a customer over a communication channel. A channel type corresponding to the communication channel over which the support request was received is identified. Which of a plurality of support specialists is assigned to service the support request over the channel type is identified. Contact information, corresponding to the channel type, for the identified support specialist is determined. The support request is forwarded to the identified support specialist based on the contact information corresponding to the channel type of the communication channel.

A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.