Automated Interaction Flow Map Generation for Agent Training

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Solution Overview

Problem

Manual generation of interaction flow maps for customer support agents is slow, laborious, prone to errors, and not suited for training automated chat agents, leading to delayed deployment and inefficiencies in customer interaction.

Innovation Solution

A computer-implemented method and apparatus that automatically transforms raw transcripts into interaction summaries, derives intent-based clusters, and generates interaction flow maps to facilitate agent training, enabling automated generation of comprehensive and accurate conversational flows for training both human and automated agents.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If manual generation of interaction flow maps is used, then agents can be trained with comprehensive interaction flows, but the process is slow and laborious

Engineering Contradiction:

Improveaccuracy of interaction flow mapsVSAvoidspeed of generating interaction flow maps

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The patent replaces the manual mechanical process of creating interaction flow maps with an automated computer-based system. The processor automatically generates interaction flow maps by analyzing interaction data, eliminating the need for manual effort while maintaining comprehensive coverage of customer interactions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service generation of interaction flow maps by automatically processing and analyzing interaction data without human intervention. The processor independently creates accurate flow maps by extracting patterns from historical interactions, reducing dependency on manual labor.

Inventive Principle:

Principle #25Self-service

2Manufacturing precision

If manual generation of interaction flow maps is used, then detailed interaction flows can be created, but errors are prone and modifications are time-consuming

Engineering Contradiction:

Improvedetail accuracy of interaction flowsVSAvoidtime for modifications and deployment

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent replaces manual creation and modification processes with automated computer-based generation. The system continuously processes interaction data to generate accurate flow maps, eliminating human errors and enabling rapid modifications through automated updates rather than manual editing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs preliminary analysis of interaction data to pre-generate accurate interaction flow maps before they are needed for training. By continuously updating the maps in advance based on new interaction patterns, the system ensures accuracy is maintained without requiring time-consuming manual revisions.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If automated chat agents are trained using manually generated flow maps, then deployment is delayed, but training accuracy can be maintained

Engineering Contradiction:

Improvetraining quality for automated agentsVSAvoiddeployment time of chat bots

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces manual flow map generation with automated computer-based generation, enabling rapid creation and updating of training data for chat agents. This automation maintains training quality through consistent analysis of interaction patterns while dramatically reducing the time required to prepare and deploy automated agents.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables continuous generation and updating of interaction flow maps, allowing training data to be constantly refreshed with new interaction patterns. This continuous process ensures chat agents receive up-to-date training without deployment delays, maintaining high reliability while accelerating time-to-market.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS11328175B2Method and apparatus for facilitating training of agents

Publication Date: 2022.05.10 24 7 AI INC

AI summary

A method and apparatus for facilitating training of agents is disclosed. Raw transcripts representing textual form of interactions between the agents and customers of the enterprise are transformed to generate transformed transcripts. An interaction summary is generated in relation to each transformed transcript. A plurality of intent-based interaction clusters are derived using the interaction summary generated in relation to each transformed transcript. The plurality of interactions are classified based on the plurality of intent-based interaction clusters and an interaction flow map is generated for each intent-based interaction cluster based on the interactions classified into the respective intent-based interaction cluster. The generated interaction flow map is capable of facilitating training of agents for interacting with the customers of the enterprise.