Customer Support Ticketing Agent

Workflow

Artificial Intelligence

Intermediate

Use Template

This is a 'Workflow' template which means that it is a single standalone workflow.

Some workflow templates can be modified to work with other workflow templates - e.g. to convert a data sync between two services from uni-directional to bi-directional

Custom Support Ticketing Agent

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Overview

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This accelerator enables you to create an AI-powered CS agent that searches across multiple sources to provide comprehensive answers to your team's questions, leaves comments on tickets in Zendesk, and updates tickets in Zendesk. The agent combines knowledge across sources to deliver accurate, contextualized responses and augment your support team.

Key Features

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• Public Documentation Search: Leverage your organization's public documentation

• Intelligent Response Generation: Uses advanced LLMs to synthesize information from multiple sources

• Zendesk Deployment: The agent is deployed directly to Zendesk so it runs asynchronously anytime a new ticket is created

• Standard Operating Procedures: Use Google docs as a source of truth for your procedures and FAQs to give the agent easy access to a living document used by the team.

Prerequisites

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1. Before implementing this template, you will need:

   1. To make sure your organization has this AI feature enabled (Admin access required)

   2. Access to a Tray.io instance with API credentials

   3. URLs for your public documentation

   4. Authentication credentials for Zendesk

   5. Authentication credentials for Google Docs

Getting Live

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Initial Setup

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1. Create a new project

2. Select "Merlin Agent Builder"

3. Select the Support Ticket Agent accelerator

4. Create or select required authentications

Configure Knowledge Sources

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1. Scrape your Public Documentation

   1. Add documentation URLs to the scraping form or the manual scraping workflow

   2. Set up crawling depth

2. Google Docs

   1. Add your Google Docs API credentials

Deploy the Agent

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1. Enable the main workflow

2. Test with sample queries

3. Monitor performance and adjust the system prompt as needed

Key Workflow Components

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Knowledge Processing

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• Documentation Crawler: Indexes public documentation

• Vector Creation: Generates embeddings for all content

• Knowledge Storage: Manages vector database operations

Query Processing

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• Query Understanding: Agent reasons over the user questions

• Response Generation: Synthesizes information into coherent answers

• Session Management: Maintains context across invocations of the agent that are related

Best Practices

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1. Regularly update your knowledge base

2. Monitor and adjust RAG thresholds (both in the knowledge tool)

3. Review and refine response quality

4. Implement feedback loops for continuous improvement

5. Add more tools that have access to internal knowledge (CRM, Internal Documentation, etc)

6. Run evaluations - you can follow our guidance here