How to Build an Efficient ChatGPT Knowledge Base

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How to Build an Efficient ChatGPT Knowledge Base

Table of Contents

  • Introduction
  • The Challenge of Support Queries
  • The Need for Automation
  • Introducing AI Co-Pilot
  • Setting up the Context Menu
  • Integrating Google Sheets
  • Training Chat GPT Model
  • Filtering and Processing Data
  • Retrieving the Response
  • Displaying the Recommendations
  • Conclusion

Introduction

In today's fast-paced world, customer support teams often find themselves overwhelmed with the volume of queries they receive. It can be time-consuming and frustrating to manually navigate through multiple applications to find the information needed to respond to customer inquiries. However, with the help of AI technology, support teams can streamline their workflow and provide faster, more efficient assistance to customers. This article will explore the use of AI Co-Pilot, a chatbot powered by Chat GPT and Pixie Brick, to automate the process of retrieving Relevant information for support queries.

The Challenge of Support Queries

Support teams frequently encounter common queries from customers who are seeking assistance with their orders, account status, or other issues. These questions often have standard answers or articles that provide the necessary information. However, support agents need a quick and easy way to access these articles without having to manually search through various applications and databases.

The Need for Automation

To make the support team's job easier and more efficient, there is a need for a solution that can retrieve relevant articles or information with just a few clicks. This solution should work seamlessly in the background, utilizing AI technology to pull data from a centralized source and provide Instant responses to support queries.

Introducing AI Co-Pilot

AI Co-Pilot, developed by Pixie Brick, is a powerful tool that integrates with popular support applications, such as Gmail, ServiceNow, or ZenDesk. It adds a context menu option that allows support agents to quickly access relevant information for customer queries. By leveraging Chat GPT, an AI language model, AI Co-Pilot can provide accurate and contextual responses to support tickets.

Setting up the Context Menu

To enable AI Co-Pilot, support agents need to add a context menu option in their web application. This context menu will be accessible by right-clicking on relevant text, such as a customer's query. By clicking on the AI Co-Pilot option, the system will initiate a process to retrieve the necessary information.

Integrating Google Sheets

For this demonstration, we will use a Google Sheet as a source of frequently asked questions (FAQs) and their corresponding answers. The support team can maintain this sheet by adding or updating FAQs as needed. To integrate the Google Sheet, we utilize the Lookup Google Sheet Row brick. This brick connects to the user's Google account and retrieves the FAQs from the specified sheet.

Training Chat GPT Model

To provide accurate responses to customer queries, we need to train the Chat GPT model with the FAQ data from the Google Sheet. The Chat Response with Chat GPT brick facilitates this training. We provide a prompt that includes the titles of the knowledge-Based articles. By feeding this prompt to Chat GPT, we train the model to recommend the most relevant article title for a given customer support ticket.

Filtering and Processing Data

Once the response from Chat GPT is generated, we need to filter the data to extract the recommended article titles. The JQ JSON processor brick is used to filter the rows based on the titles and store them in a variable for further processing. The filtered rows are then passed to the Chat GPT output, where the final responses are stored.

Retrieving the Response

At this stage, we have the responses from Chat GPT stored in the article object. To display them in a user-friendly manner, we need to add a brick called Sidebar Display Temporary Information. This brick allows us to configure the content to be displayed in the sidebar, including the header and body sections. We can customize the appearance and include buttons or additional elements for better user experience.

Displaying the Recommendations

By running the configured flow, the AI Co-Pilot system will retrieve the responses from Chat GPT and display them in the sidebar. The recommendations will include the article titles, account order status, and other relevant information. A "Copy to Clipboard" button can be added to facilitate easy sharing of the response with the customer.

Conclusion

AI Co-Pilot, powered by Chat GPT and Pixie Brick, provides an efficient solution for support teams to handle customer queries. By integrating with popular web applications, such as Gmail or ZenDesk, it enables support agents to quickly access relevant information and provide accurate responses. This automation streamlines the support process, saves time, and enhances customer satisfaction. With AI Co-Pilot, support teams can focus on delivering better service, while AI technology handles the repetitive tasks of retrieving information.

FAQ

Q: What applications can AI Co-Pilot integrate with?
A: AI Co-Pilot can integrate with popular support applications, such as Gmail, ServiceNow, ZenDesk, and others. It adds a context menu option that allows support agents to access relevant information with a single click.

Q: Can I customize the responses generated by Chat GPT?
A: Yes, you can train the Chat GPT model with your own data to provide customized responses. By using the JQ JSON processor and the Chat Response with Chat GPT bricks, you can filter, process, and retrieve the responses that best fit your support requirements.

Q: Can AI Co-Pilot handle multiple languages?
A: AI Co-Pilot can be trained to handle multiple languages. By providing the appropriate training data and configuring the language settings, you can create a multilingual support system.

Q: Is AI Co-Pilot suitable for small support teams?
A: Absolutely! AI Co-Pilot is designed to assist support teams of all sizes. It automates the process of retrieving information, saving time and effort for support personnel. Small support teams can greatly benefit from its efficiency and accuracy.

Q: Is the information stored in the sidebar display temporary?
A: Yes, the information displayed in the sidebar is temporary and specific to each support query. It is dynamically generated based on the customer's inquiry and can be easily shared or copied to the clipboard for further use.

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