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Ask a Human

This workflow builds an intelligent AI customer service agent capable of automatically answering user inquiries. When the AI is not confident in its response, the system checks if the user has provided an email address; if so, it notifies a human customer service representative via Slack, enabling a seamless transition between AI and human support. Additionally, it employs window buffer memory management to maintain conversation context, enhancing the interaction experience. This workflow effectively addresses the bottlenecks faced by AI customer service when dealing with complex issues, ensuring timely resolution of inquiries and improving customer satisfaction and service efficiency.

Workflow Diagram
Ask a Human Workflow diagram

Workflow Name

Ask a Human

Key Features and Highlights

This workflow builds an intelligent AI customer service agent capable of automatically answering user inquiries. When the AI lacks confidence in its response, the system invokes a custom tool to trigger a subsequent process that checks whether the user has provided an email address. If an email is provided, the issue and user information are automatically forwarded to human agents via Slack notifications, enabling seamless integration between AI and human support. Additionally, the workflow employs a windowed buffer memory to manage conversational context, enhancing interaction quality and response accuracy.

Core Problem Addressed

This solution tackles the bottleneck faced by AI customer service when handling complex or uncertain queries, preventing the AI from giving blind or inaccurate answers that degrade user experience. By automatically detecting the user’s email and escalating to human agents, it ensures timely and effective issue resolution, thereby improving customer satisfaction and service efficiency.

Application Scenarios

  • Customer service automation, especially suited for product inquiries, technical support, and other scenarios requiring multi-turn conversations.
  • Hybrid service environments where AI and human agents collaborate.
  • Enterprises aiming to reduce customer service workload through automation while guaranteeing human intervention for complex issues.

Main Workflow Steps

  1. The user initiates a query via the chat interface.
  2. The AI agent (powered by GPT-4) attempts to answer the user’s question.
  3. If the AI is uncertain about the answer, it calls the “Not sure?” tool to trigger a sub-workflow.
  4. The sub-workflow checks if the user input contains an email address.
  5. If an email is detected, a notification is automatically sent to the human support channel on Slack, alerting that assistance is needed.
  6. If no email is provided, the user is prompted to supply their email and resubmit the query.
  7. After human agent intervention, the system confirms successful notification and responds to the user.
  8. Throughout the conversation, a windowed buffer memory maintains context continuity.

Involved Systems and Services

  • OpenAI GPT-4 model (AI language model)
  • Slack (human agent notification)
  • n8n sub-workflow mechanism and conditional nodes
  • Webhook-triggered chat interface
  • Code nodes for email validation and custom responses

Target Users and Value Proposition

This workflow is designed for enterprises and teams seeking to enhance customer service intelligence by combining AI and human collaboration. It is particularly beneficial for customer support teams aiming to reduce repetitive tasks through automated responses while ensuring complex issues receive human follow-up. By implementing this workflow, organizations can significantly improve response speed, customer satisfaction, and optimize the allocation of support resources.