Live-Monitoring Agent Instances for Dynamic Threshold Control

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Solution Overview

Problem

Conventional contact centers lack the ability to continuously optimize agent instance performance thresholds, leading to inefficiencies in handling customer interactions and increased energy consumption due to manual threshold adjustments that are not regularly updated based on changing conditions.

Innovation Solution

A management network system that utilizes artificial intelligence and machine learning to analyze historical data and adjust agent instance performance thresholds dynamically, optimizing interaction times and reducing the need for manual intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual monitoring and adjustment of agent performance thresholds is used, then operational control is maintained, but efficiency deteriorates and energy consumption increases due to lack of continuous optimization

Engineering Contradiction:

Improvecontact center efficiencyVSAvoidenergy consumption

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system enables automated self-adjustment of agent performance thresholds through AI/ML algorithms that continuously learn from historical data and changing conditions. The management network automatically modifies thresholds without manual intervention, allowing the system to self-optimize agent instance performance and reduce energy consumption while maintaining productivity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements continuous feedback loops where agent instance performance data is collected, analyzed by AI/ML models, and used to dynamically adjust performance thresholds. This closed-loop feedback mechanism ensures thresholds remain optimized according to actual performance patterns and changing business conditions, improving efficiency while reducing wasted energy on suboptimal configurations.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If static performance thresholds are used, then system simplicity is maintained, but adaptability deteriorates as conditions change over time

Engineering Contradiction:

Improvethreshold optimizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system transitions from static to dynamic threshold management by implementing AI/ML-driven automated adjustment mechanisms. Performance thresholds are continuously adapted based on real-time data analysis and changing business conditions, enabling the system to respond dynamically to new patterns while maintaining operational effectiveness.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent replaces manual mechanical adjustment processes with automated AI/ML-based electronic systems. Instead of manual monitoring and threshold setting, the system uses machine learning algorithms to automatically analyze performance data and adjust thresholds, reducing operational complexity while significantly improving adaptability to changing conditions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If more computing devices are deployed to handle increased interactions, then interaction handling capacity increases, but energy consumption increases proportionally

Engineering Contradiction:

Improveinteraction handling capacityVSAvoidenergy consumption

Core Design Contradiction:

ProductivityVSUse of energy by stationary object

Solution Approach 1:

The system optimizes the parameter of agent instance performance thresholds to maximize interaction handling capacity while minimizing energy consumption. By dynamically adjusting thresholds based on AI/ML analysis of performance data, the system achieves higher productivity with fewer computing resources, reducing the need to deploy additional energy-consuming devices.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12418451B2Live-monitoring to trigger agent instance modification actions via an in-house management network

Publication Date: 2025.09.16 INTRADIEM INC

AI summary

A computer-implemented method for managing a contact center one or more processors in a management network (a) receiving, from an end-user network, data associated with a plurality of agent instances servicing incoming communications for the contact center, wherein the contact center, the end-user network, and the management network are associated with the enterprise; (b) determining, based on a specification of a logical directive, an operation to be performed in relation to the plurality of agent instances, the specification of the logical directive having at least one condition that, if satisfied by the received data associated with the plurality of agent instances servicing the incoming communications for the contact center, defines the operation to be performed; and (c) providing, to one or more servers, the determined operation to be performed, wherein the operation includes making a modification relating to (i) at least one of the plurality of agent instances and/or (ii) the servicing of the incoming communications. A computing system and article of manufacture are also provided.