AI Contact Center Agent for Cross-Center Request Resolution
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Solution Overview
Problem
Conventional contact center services are designed without a mechanism to seamlessly transfer a user from a first contact center associated with one entity to a second contact center associated with another entity during an engagement, leading to inefficiencies and additional engagement requirements when the initial contact center is incapable of addressing the user's issue.
Innovation Solution
A system that enables seamless integration of a second contact center into the first contact center's interface, allowing users to communicate with both centers without disconnecting, using software that can determine the need for a second contact center and facilitate a unified communication experience through machine learning and online learning techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional contact center services are designed without a transfer mechanism, then each contact center operates independently with clear boundaries, but users cannot be seamlessly transferred between contact centers when the initial center cannot address their issue
Solution Approach 1:
An intermediary software service is introduced between the first and second contact centers to facilitate seamless transfer. This intermediary manages the integration, routing, and coordination between different contact center systems without requiring complex direct integration between them, thus enabling adaptability while controlling system complexity.
Solution Approach 2:
The contact center system is designed with universal interfaces and protocols that allow it to interact with multiple different contact center types and vendors. This multi-functionality enables the system to transfer users between different contact centers while maintaining a consistent user experience and manageable architecture.
2Ease of operation
If multiple separate engagements are required when switching contact centers, then clear accountability and service boundaries are maintained, but user experience deteriorates due to disconnection and repetition
Solution Approach 1:
The system maintains continuity of the contact center engagement by keeping the user connected to the original contact center interface while seamlessly integrating the second contact center. This allows the useful action of problem-solving to continue without interruption, preventing user disconnection and eliminating the need for repeated information provision.
Solution Approach 2:
The first and second contact centers are merged into a unified engagement experience where users interact with a single integrated system. This merging combines the capabilities of both contact centers while maintaining a single continuous user session, improving ease of operation and eliminating time loss from multiple separate engagements.
3Adaptability or versatility
If contact center services are integrated seamlessly, then user experience is improved with single-point access, but system complexity and integration requirements increase
Solution Approach 1:
An intermediary software service acts as a mediator between different contact center systems, handling the complex integration requirements centrally. This intermediary manages data exchange, protocol translation, and coordination between systems, enabling seamless integration capability while containing integration complexity in a dedicated component rather than distributing it throughout the entire system.
Data Source
AI summary
A user of a user device initiates a contact center engagement with a first contact center. The first contact center processes a prompt received, by a first contact center software service associated with a first entity. Determine, by the first contact center software service and based on stored data associated with the prompt or an account of the contact center user device, that the prompt relates to a second contact center software service associated with a second entity. Train, using online learning techniques, an artificial intelligence agent of the first contact center software service based on prior responses received from the second contact center software service during a merged contact session. The artificial intelligence agent is capable of providing a resolution to a user of the contact center user device without contacting the second contact center software service after a response is provided to questions in the merged contact session.


