Building and Scaling Workflows with HALO

Introduction

Now that you’ve prepared your workflow and mapped out your processes, it’s time to bring your AI Agent to life with HALO. HALO’s agentic AI allows you to design intelligent agents that handle customer interactions seamlessly, whether through email, chat, or phone.

This article will guide you through the process of building your AI Agent in HALO and show you how to scale its capabilities to handle more complex tasks. For a practical demonstration of these concepts, including real-world examples, watch the embedded webinar at the end of this article.

How to Build an AI Agent in HALO

Step 1: Translate Your Workflow into HALO

Your workflow serves as the blueprint for your AI Agent. Use HALO’s interface to define the key components of your agent’s behavior:

• Triggers: What starts the process?
  Example: A customer asks for their shipping status via chat.

• Actions: What happens next?
  Example: The AI Agent retrieves the tracking number from the CRM and checks the shipping provider’s system.

• Outputs: What is the final result?
  Example: The AI Agent provides the shipping status to the customer in real time.

By translating your workflow into HALO, you can ensure your AI Agent is structured to handle tasks efficiently and effectively.

Step 2: Use HALO’s Agentic AI

HALO’s agentic AI is designed to handle complex tasks that require decision-making, context, or integration with external systems. More documentation on HALO's AI Agents and it’s possibilities can be found here.

Examples of What HALO’s AI Can Do:

• Summarize Customer Feedback: Analyze feedback from multiple channels and group it into actionable themes.

• Retrieve Shipping Statuses: Access external systems to provide real-time updates to customers.

• Analyze Unstructured Data: Extract key information from emails, chats, or calls.

Example Use Case:

A customer asks, “Where is my package?” HALO’s AI Agent:

1. Ask for a tracking number at the user.

2. Retrieves the shipping status using tool [TOOL].

3. Responds to the customer with the shipping update in a friendly, conversational tone.

By leveraging HALO’s AI capabilities, you can design agents that go beyond simple automation to deliver intelligent, context-aware responses.

Step 3: Test and Refine

Once your AI Agent is built, it’s essential to test it thoroughly to ensure it performs as expected.

What to Look For During Testing:

• Errors or Inconsistencies: Are there any gaps in the agent’s responses or actions?

• Simplification Opportunities: Can any steps be streamlined or removed?

• Automation Potential: Are there additional tasks the agent could handle?

Tips for Refinement:

• Gather feedback from team members or customers who interact with the AI Agent.

• Use HALO’s analytics tools to monitor the agent’s performance and identify areas for improvement.

• Iterate on the agent’s design to enhance its capabilities over time.

Scaling Your AI Agents with HALO

Mixing Deterministic and Probabilistic Steps

As you scale your AI Agent, you may need to combine rule-based (deterministic) steps with AI-driven (probabilistic) decision-making.

Example:

• Deterministic Steps: Use rule-based automation for structured tasks, such as copying data from one system to another.

• Probabilistic Steps: Use HALO’s AI for tasks that require interpretation or context, such as analyzing customer feedback or generating personalized responses.

This hybrid approach ensures your AI Agent is both reliable and flexible, capable of handling a wide range of tasks.

Advanced Tips for Building and Scaling AI Agents in HALO

1. Write Effective Prompts
   HALO’s AI relies on clear instructions to perform tasks accurately. When designing your agent, write detailed prompts that specify:

   • The agent’s role (e.g., “You are a customer support assistant.”).

   • The task it needs to perform (e.g., “Retrieve the shipping status for the provided tracking number.”).

   • The tone or style of the response (e.g., “Respond in a friendly and professional tone.”).

   • For more information, check out this course on AI Prompting.

2. Integrate with Systems
   HALO’s agentic AI can connect to external systems like CRMs, databases, or shipping platforms. This enables your AI Agent to:

   • Retrieve real-time data (e.g., shipping statuses, order details).

   • Update records automatically (e.g., logging customer interactions in the CRM).

   • Provide seamless, end-to-end customer support.

Conclusion

Building AI Agents with HALO is a game-changer for automating customer interactions and scaling your operations. By starting with a clear workflow, leveraging HALO’s agentic AI, and testing thoroughly, you can create agents that save time, reduce errors, and enhance customer satisfaction.

As your confidence grows, you can scale your AI Agents to handle more complex tasks, combining rule-based automation with AI-driven decision-making for maximum flexibility and efficiency.

Watch the Webinar

For a practical demonstration of these concepts, watch the webinar below. In this session, we explore how to build and refine an AI Agent, structure workflows, and implement guardrails to ensure your agent performs effectively.