Personalized Automated Agent for Urgent Communication Handling
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Solution Overview
Problem
Digital workers face challenges when unavailable, as automatic replies lack personalization and may not address urgent issues effectively, leading to user frustration and increased network traffic.
Innovation Solution
A personalized automated agent system that generates responses based on the agent owner's context, using a knowledge database and sentiment analysis to determine urgency and provide tailored interactions, reducing the need for direct communication with the agent owner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional automatic replies are used, then basic information can be provided to contacts, but the responses lack personalization and cannot address urgent issues effectively
Solution Approach 1:
An automated agent is introduced as an intermediary between the digital worker and contacts. The agent accesses a knowledge database containing the worker's context information and generates personalized responses on behalf of the worker, resolving the contradiction by providing adaptability without requiring the worker to manually craft each response.
Solution Approach 2:
The system creates copies of the digital worker's context and communication patterns stored in a knowledge database. The automated agent uses these copies to generate responses that mimic the worker's personal communication style, achieving personalization without the complexity of real-time analysis of the worker's entire communication history.
2Reliability
If the digital worker monitors all incoming communications for urgent issues, then no urgent matters are missed, but the worker cannot fully disconnect during unavailable periods
Solution Approach 1:
The automated agent performs self-service by autonomously analyzing incoming communications against the knowledge database and determining urgency levels. The agent handles routine communications independently and only escalates truly urgent matters, allowing the digital worker to fully disconnect while maintaining reliable detection of critical issues through the agent's autonomous monitoring.
3Loss of information
If comprehensive information is provided in automatic replies to all contacts, then all possible questions are answered, but the information becomes impractical and difficult for contacts to process
Solution Approach 1:
The automated agent applies local quality by tailoring the amount and type of information provided to each specific contact based on their needs and the nature of their communication. Rather than providing comprehensive information to everyone, the agent selectively retrieves and presents only the relevant information from the knowledge database for each interaction, making information both complete and accessible.
4Productivity
If the digital worker responds promptly to all communications, then user satisfaction is maintained, but the worker experiences anxiety and cannot take personal time
Solution Approach 1:
The system performs preliminary action by pre-processing and organizing the digital worker's context information into a structured knowledge database before communications occur. When communications arrive, the automated agent can quickly retrieve and generate appropriate responses without requiring the worker's immediate attention, maintaining high response efficiency while enabling the worker to disconnect.
Data Source
AI summary
Generating an automated agent enabled to engage in a multi-turn discussion with a user in response to a received request. For example, the automated agent is operative to provide a response on behalf of an agent owner. A knowledge database is generated based on the agent owner's context (e.g., email conversations, calendar data, organizational chart, document database). A request for information is received and analyzed for understanding the request and for gauging a level of frustration of the requesting user. An urgency level of the request is determined based at least in part on the level of frustration of the requesting user. A query of the knowledge database is made for determining a response to the request, wherein the determined response is based at least in part on the urgency level of the request. A response is generated and provided to the requesting user.