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Agent Playbook

Browse agentic AI tasks that instruct LLMs to carry out specific jobs.
These can be integrated into existing workflows in your apps and tools.

Fintech

Marketplace

Insurance

Legal and Compliance

Engineering

Sales

Support

Claims Policy Verification

Claims Policy Verification

Claims Triage

Claims Triage

Claims Fraud Analysis

Claims Fraud Analysis

Customer Query Categorisation

Customer Query Categorisation

Policy Comparison

Policy Comparison

Damage Assessment from Images

Damage Assessment from Images

Insurance Needs Analysis

Insurance Needs Analysis

Policy Renewal Recommendation

Policy Renewal Recommendation

Claims Status Update

Claims Status Update

Compliance Documentation Check

Compliance Documentation Check

Claims Documentation Validation

Claims Documentation Validation

Query Triage and Escalation

Query Triage and Escalation

Customer Support

Customer Query Categorisation

This agentic task categorises and prioritises insurance customer enquiries - useful for customer service agents. The task specification outlines how to:

  • Classify enquiries across multiple communication channels using semantic analysis

  • Calculate priority scores based on urgency, complexity and service level agreements

  • Generate routing recommendations with department-specific handling protocols

  • Identify recurring enquiry patterns through trend analysis

  • Produce structured service analytics with volume-based insights


As a modular agentic task, it can be integrated into CRM systems and helpdesk platforms, enabling AI agents to execute systematic enquiry management within existing customer service workflows. The task specification includes frameworks for multi-channel analysis, priority assessment, routing optimisation, and trend identification, adaptable to specific insurance products and service requirements.

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Example outputs:

"response": {
    "category": "Billing",
    "priority": "High",
    "department": "Billing Department",
    "subcategory": "Duplicate Charge",
    "auto_response": "Thank you for reaching out to us. We apologize for any inconvenience caused by the duplicate charge on your account. Our team is currently investigating the issue and will ensure that any necessary refunds are processed promptly. We appreciate your patience.",
    "suggested_action": "Investigate the duplicate charge on the customer's account and process a refund if applicable. Contact the customer with an update on the resolution."

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Claims Fraud Analysis

Claims Fraud Analysis

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Policy Comparison

Policy Comparison