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About Harvey

Harvey, developed by Hiver, is an AI-powered sidekick that enhances team productivity by tackling time-consuming tasks and optimizing customer support workflows.

This intelligent AI assistant is designed to work seamlessly within Gmail-based helpdesk operations, using Natural Language Processing (NLP) to analyze and understand customer conversations. By identifying context and utilizing smart suggestions, Harvey empowers customer support agents to work more efficiently, resulting in improved customer satisfaction.


  • Time Savings: Harvey takes on repetitive tasks, such as suggesting relevant email templates and automatically closing non-actionable “Thank You” responses, freeing up valuable time for support agents to focus on more important tasks.
  • Enhanced Efficiency: By intelligently suggesting email templates based on customer messages, Harvey assists agents in crafting responses quickly and accurately.
  • Improved Metrics: Harvey’s ability to close conversations impacted by non-actionable responses helps maintain accurate service level agreement (SLA) metrics and performance analytics.


  • Learning Curve: While Harvey is designed to be user-friendly, integrating an AI assistant into existing workflows might require some adjustment and learning for the support team.
  • Dependency: Organizations need to ensure that the AI assistant’s actions align with the company’s support policies and guidelines.


  • Intelligent Email Templates: Harvey suggests the most relevant email templates based on customer inquiries, reducing the time needed to craft responses.
  • Thank You Detection: Harvey automatically identifies and closes conversations reopened by customers sending “Thank You” responses, preventing metric skew and allowing agents to focus on meaningful tasks.
  • Accountability Tracking: Teams can easily track conversations closed by Harvey and review actions performed by the AI assistant in the Gmail activity panel.
  • Continuous Learning: Harvey learns from agent feedback; if a conversation is reopened by an agent, Harvey utilizes the feedback to improve the accuracy of its responses.

Use Cases

  • Customer Support: Harvey’s intelligent suggestions and automated actions streamline customer support operations, enhancing agent efficiency and customer satisfaction.
  • Metrics Accuracy: By closing non-actionable conversations promptly, Harvey contributes to maintaining accurate support metrics and performance indicators.
  • Workflow Optimization: Organizations aiming to optimize support workflows and allocate resources more efficiently can benefit from Harvey’s automation.

Harvey emerges as a valuable AI assistant in the customer support landscape, demonstrating its prowess in augmenting team productivity and optimizing workflows. With its ability to suggest intelligent email templates and autonomously handle non-actionable “Thank You” responses, Harvey demonstrates its potential to enhance support agent efficiency, reduce manual tasks, and maintain accurate service metrics.

The tool’s accountability tracking ensures transparency, allowing teams to oversee Harvey’s actions and further fine-tune its performance. By continuously learning from agent feedback, Harvey adapts and improves, aligning its assistance with the evolving needs of the customer support team.

Organizations seeking to enhance customer support operations, boost efficiency, and improve support metrics can find a reliable ally in Harvey. Its integration within the Gmail ecosystem ensures easy adoption, and its impact on productivity and performance metrics make it a valuable asset in the customer support toolkit.

Overall, Harvey’s AI-powered capabilities harmonize with customer support requirements, reducing the burden of repetitive tasks and enabling agents to focus on providing exceptional customer experiences.

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