Multi-Channel Intent Engine for Automated Resolution Actions
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Solution Overview
Problem
Managing and optimizing data objects and computing resources in complex application frameworks is challenging due to the dynamic nature of inputs and components, leading to inefficient resource usage and difficulty in tracking and resolving service tickets and workflows.
Innovation Solution
Implementing an intent engine that processes multi-channel service data objects to recognize support intentions and automate resolution actions, improving resource management and data processing efficiency through intent classification and correlation with resolution data objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual management of service tickets and workflows is used in complex application frameworks, then flexibility in handling diverse communication channels is maintained, but resource utilization efficiency deteriorates and tracking resolution becomes difficult
Solution Approach 1:
The system implements self-service through automated intent classification and resolution actions. The intent engine automatically processes service messages from multiple communication channels, classifies intents, and executes resolution actions without requiring manual intervention for each ticket, thereby improving resource utilization efficiency while managing complexity through automation
Solution Approach 2:
The intent engine serves multiple functions within a single system component: receiving service messages from diverse communication channels, extracting features, classifying intents, correlating with resolution data objects, and executing resolution actions. This multi-functionality improves productivity by consolidating what would otherwise require multiple separate manual processes
2Adaptability or versatility
If multiple communication channels are integrated for service messages, then customer support coverage is improved, but data processing complexity and computational strain increase
Solution Approach 1:
The system segments the processing of multi-channel data by creating separate feature datasets for each communication channel while maintaining a unified intent classification process. Each channel's data is processed independently through feature extraction, then integrated at the intent classification stage, reducing overall processing complexity while maintaining multi-channel capability
Solution Approach 2:
The intent engine acts as an intermediary between multiple communication channels and the resolution system. It receives diverse messages from various channels, standardizes them through feature extraction and intent classification, and forwards processed intents to resolution data objects, thereby managing data processing complexity while supporting multiple channels
3Speed
If automated intent classification is implemented, then resolution speed is improved, but computing resource requirements increase
Solution Approach 1:
The system applies partial action by performing intent classification only on service messages that require resolution, rather than continuously processing all incoming data. The intent engine selectively processes messages based on their content and urgency, improving resolution speed for critical issues while reducing overall computing resource consumption
Solution Approach 2:
The intent classification process dynamically adjusts processing parameters based on input characteristics. The system modifies feature extraction depth, classification model complexity, and processing priority based on message type, channel source, and urgency indicators, thereby optimizing resolution speed while controlling computing resource consumption
4Measurement precision
If feature datasets are extracted from each service message, then classification accuracy is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary feature extraction and message preprocessing before intent classification. By preparing feature datasets in advance and organizing message data into standardized formats, the system reduces the actual classification time while maintaining high accuracy, as the heavy lifting of data preparation is completed beforehand
Data Source
AI summary
Methods, apparatuses, or computer program products provide for processing multi-channel service data objects to initiate automated resolution actions via an intent engine. A first service message object is received via a first communication channel of a plurality of communication channels. The first service message object defines a first feature dataset associated with the first communication channel. Additionally, a second service message object is received via a second communication channel of the plurality of communication channels. The second service message object defines a second feature dataset associated with the second communication channel. Based on the first feature dataset and the second feature dataset, support labels for the first service message object and the second service message object are generated. Furthermore, the support labels for the first service message object and the second service message object are correlated to respective resolution data objects related to one or more resolution actions.