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Overview

Enable your agents to manage customer support operations through Zendesk. Create and update tickets, manage users, track support metrics, and streamline your customer service workflows with AI-powered automation.

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Prerequisites

Before using the Zendesk integration, ensure you have:

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Available Tools

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Ticket Management

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User Management

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Administrative Tools

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Custom Fields

Custom fields allow you to store additional information specific to your organization:

[
  { "id": 27642, "value": "745" },
  { "id": 27648, "value": "yes" }
]

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Ticket Priority Levels

Understanding priority levels:

  • urgent - Critical issues requiring immediate attention
  • high - Important issues that should be addressed quickly
  • normal - Standard priority for most tickets
  • low - Minor issues that can be addressed when convenient

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Ticket Status Workflow

Standard ticket status progression:

  • new - Recently created, not yet assigned
  • open - Actively being worked on
  • pending - Waiting for customer response or external action
  • hold - Temporarily paused
  • solved - Issue resolved, awaiting customer confirmation
  • closed - Ticket completed and closed

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Usage Examples

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Basic Zendesk Agent Setup

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

# Get enterprise tools (Zendesk tools will be included)
enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

# Create an agent with Zendesk capabilities
zendesk_agent = Agent(
    role="Support Manager",
    goal="Manage customer support tickets and provide excellent customer service",
    backstory="An AI assistant specialized in customer support operations and ticket management.",
    tools=[enterprise_tools]
)

# Task to create a new support ticket
create_ticket_task = Task(
    description="Create a high-priority support ticket for John Smith who is unable to access his account after password reset",
    agent=zendesk_agent,
    expected_output="Support ticket created successfully with ticket ID"
)

# Run the task
crew = Crew(
    agents=[zendesk_agent],
    tasks=[create_ticket_task]
)

crew.kickoff()

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Filtering Specific Zendesk Tools

from crewai_tools import CrewaiEnterpriseTools

# Get only specific Zendesk tools
enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token",
    actions_list=["zendesk_create_ticket", "zendesk_update_ticket", "zendesk_add_comment_to_ticket"]
)

support_agent = Agent(
    role="Customer Support Agent",
    goal="Handle customer inquiries and resolve support issues efficiently",
    backstory="An experienced support agent who specializes in ticket resolution and customer communication.",
    tools=enterprise_tools
)

# Task to manage support workflow
support_task = Task(
    description="Create a ticket for login issues, add troubleshooting comments, and update status to resolved",
    agent=support_agent,
    expected_output="Support ticket managed through complete resolution workflow"
)

crew = Crew(
    agents=[support_agent],
    tasks=[support_task]
)

crew.kickoff()

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Advanced Ticket Management

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

ticket_manager = Agent(
    role="Ticket Manager",
    goal="Manage support ticket workflows and ensure timely resolution",
    backstory="An AI assistant that specializes in support ticket triage and workflow optimization.",
    tools=[enterprise_tools]
)

# Task to manage ticket lifecycle
ticket_workflow = Task(
    description="""
    1. Create a new support ticket for account access issues
    2. Add internal notes with troubleshooting steps
    3. Update ticket priority based on customer tier
    4. Add resolution comments and close the ticket
    """,
    agent=ticket_manager,
    expected_output="Complete ticket lifecycle managed from creation to resolution"
)

crew = Crew(
    agents=[ticket_manager],
    tasks=[ticket_workflow]
)

crew.kickoff()

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Support Analytics and Reporting

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

support_analyst = Agent(
    role="Support Analyst",
    goal="Analyze support metrics and generate insights for team performance",
    backstory="An analytical AI that excels at extracting insights from support data and ticket patterns.",
    tools=[enterprise_tools]
)

# Complex task involving analytics and reporting
analytics_task = Task(
    description="""
    1. Search for all open tickets from the last 30 days
    2. Analyze ticket resolution times and customer satisfaction
    3. Identify common issues and support patterns
    4. Generate weekly support performance report
    """,
    agent=support_analyst,
    expected_output="Comprehensive support analytics report with performance insights and recommendations"
)

crew = Crew(
    agents=[support_analyst],
    tasks=[analytics_task]
)

crew.kickoff()