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Workflow Overview
Key Benefits Demonstrated
Multi-Channel Customer Support
Multi-Channel Customer Support
In this example, a Manager Agent orchestrates a customer support workflow across chat, email, and SMS channels, dynamically routing tasks to specialized agents based on user preferences and message content.
Workflow Overview
User Inquiry Intake
The Manager Agent receives an incoming support request via the primary channel (chat, email, or SMS).
Channel Classification
A sentiment analysis worker agent evaluates the message tone and urgency.
If negative sentiment or high urgency is detected, prioritize chat or SMS for real-time engagement.
Intent Detection & Routing
An NLU agent parses the request to identify intent (e.g., billing, technical issue, feature request).
The Manager Agent maps the intent to the appropriate domain specialist agent (Billing Agent, Tech Support Agent, Product Feedback Agent).
Contextual Response Generation
The chosen worker agent generates a draft response, leveraging the Knowledge Base for relevant documentation or past resolutions.
Approval & Escalation
For sensitive cases (e.g., account closures), the Manager Agent routes the draft to a human supervisor agent for review.
Based on the supervisor’s decision, the final response is sent via the user’s preferred channel.
Follow-up & Logging
After resolution, a follow-up task is scheduled to check user satisfaction.
All interactions, metrics, and context are logged in Long-Term Memory for future personalization.
Key Benefits Demonstrated
Adaptability
: Dynamically switches channels for optimal user experience.
Scalability
: Distributes workload across multiple worker agents to handle high volumes.
Resilience
: Implements fallback to human review for edge cases.
Personalization
: Leverages memory and KB context for tailored responses.
Assistant
Responses are generated using AI and may contain mistakes.