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Understand AI Agents

Last Update: Nov 2024 • Est. Read Time: 4 MIN
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AI Agents are designed to automate conversations and improve customer interactions. By leveraging advanced artificial intelligence, AI Agents seamlessly resolve issues and perform actions with human-like decision-making, resulting in faster resolutions and happier customers. 

Benefits of AI Agents:

  • 24/7 customer support: Ensure queries are handled at all times, enhancing customer satisfaction and loyalty, especially in retail and e-commerce environments.
  • Reduced wait times:  Streamline processes like ordering to minimize delays.
  • Multilingual support: Communicate with customers in multiple languages, allowing you to support a global customer base.
  • Multi-channel availability to provide support across chat, email, SMS, WhatsApp, and Kustomer Voice.

...and more!

Who can access this feature?
User typesAdmins can access the AI Agents Team page.


In this article:

This article introduces the main concepts you need to understand and build an AI Agent team for your organization. To learn more about configuring an AI Agent team, see our Kustomer University course.

What powers AI Agents?

AI Agents are powered by our reasoning engine, which thinks like a human to make decisions. It adapts to new information customers provide, handling uncertainty and generating dynamic responses based on changing contexts.

AI Agent Teams

AI Agent teams are customizable to suit your organization's needs. When creating a team, consider what problems or challenges you want the agents on that team to address. You may also want to create teams based on the channels they’ll respond to, such as chat, email, or SMS, to ensure tailored responses for each channel. If your organization manages multiple brands, you can also create a separate, dedicated team for each brand, ensuring that each one maintains its unique voice and tone while responding to inquiries related to its products or services. 

How AI Agents work

AI Agents are autonomous and intelligent systems that use Large Language Models (LLMs) to help answer customer questions and solve problems. They work together as a team, alongside your human agents, to resolve customer inquiries.

AI Agents work in an iterative cycle, meaning they process new information as it comes in and adjust their actions as needed. They use tools to interact with the system and take actions based on the conversation. These actions can include things like looking up customer details or updating order information both inside and outside of Kustomer.

When setting up an AI Agent, you decide its job, how it should respond, and what tools it can use. For example, let's say you are setting up an AI Agent for an airline's customer support call center. These agents would interact with reservation databases and ticketing systems found in your call center system. The AI Agents can then use tools to perform actions such as changing flight bookings or handling cancellations.

Supervisor agent

When you create a new AI agent team, a "supervisor" agent is automatically added. This agent greets customers and is the only one that talks to them directly. It can access tools and your knowledge base to perform needed actions and provide helpful answers. The supervisor agent also works with other AI agents on the team to gather the necessary information and take appropriate actions to resolve customer issues.

Tools

Each AI Agent should be equipped with the tools needed to take relevant actions and resolve customer inquiries. Examples of tools an AI agent can use include access to customer data, product inventory, or order history. You have control over which tools an agent can use and when, ensuring they have the right resources to assist customers. 

This tutorial provides examples of AI Agents and tools you can consider using to respond to e-commerce inquiries.

Knowledge

AI Agents can leverage your organization’s public knowledge base(s) to respond accurately to customer inquiries. By tapping into your existing knowledge base, AI Agents enhance the consistency of your customer support. They can quickly locate the most relevant information, reducing the time it takes to resolve issues and providing customers with clear and accurate responses. 

Learn how to build a team that uses your knowledge base to respond to customer inquiries in this tutorial.

Observability

The Traces page provides detailed logs of interactions between AI Agents and customers. Traces help you monitor an AI Agent team's performance, understand its decision-making, and identify areas for improvement.

Traces include details such as:

  • Timestamps of each step in the interaction.
  • Inputs received from the customer, such as messages.
  • The name of the tool that was used to respond
  • Outputs sent back to the customer, such as replies.
  • The help article used to respond 

Learn more about observability and how to read a trace in this article.

Guardrails

Guardrails are crucial for ensuring that your AI agents adhere to company policies, particularly when it comes to sensitive topics like competitors. By setting guardrails, you can prevent your AI agents from mentioning or discussing competitors in customer interactions. In addition to protecting against mentions of competitors, these guardrails work alongside standard safeguards within the product to ensure AI agents don’t disclose sensitive information. 

Guardrails can also be used strategically to amplify the benefits and unique differentiators of your products and services. By setting these guidelines, you help your AI agents maintain focus on brand integrity and consistently communicate the value your products and services bring to customers.

Reporting

The AI Agents standard report lets you track the quality of responses generated by AI Agents and track key metrics such as the number of conversations they handle. This report helps you evaluate the effectiveness of your AI Agents and identify opportunities to optimize their performance.