Preparing to Build Your First Workflow with HALO

Introduction

Imagine an AI Agent that not only answers customer questions but also retrieves real-time data, updates your CRM, and provides personalized recommendations—all while saving you time and resources. With HALO, this is possible, but preparation is the foundation of success. Without a clear plan, you risk creating an AI Agent that is inefficient, incomplete, or unable to meet your business needs.

Workflows are the key to ensuring your AI Agent is designed to handle tasks effectively. By mapping out processes and clarifying tasks, workflows act as a blueprint for your AI Agent, helping it deliver real value and integrate seamlessly into your operations. More about this topic, in this article. Here, we will guide you through the preparation phase, ensuring you’re ready to design an AI Agent that meets your business needs.

Why Preparation Matters

Think of workflows as the foundation of your AI Agent’s success. Without a clear understanding of the steps or inputs required, the result can be chaotic. Workflows help you:

• Identify the right tasks for your AI Agent to handle.

• Map out the steps in your process to ensure nothing is missed.

• Leverage HALO’s agentic AI capabilities effectively.

Preparation is like onboarding a new colleague. You wouldn’t hire someone without providing a clear job description, the right tools, and proper training. Similarly, your AI Agent needs a well-defined role and structure to succeed. By preparing thoroughly, you’ll save time, reduce errors, and ensure your AI Agent is set up for success.

Step-by-Step Guide to Preparing an AI Agent in HALO

Step 1: Define Your Use Case

Start by identifying a small, simple task that your AI Agent can handle. Focus on tasks that are repetitive, time-consuming, or prone to errors.

Example: Retrieving the shipping status of a package for customers.

Ask Yourself:

• What triggers the task? (e.g., a customer asks for their shipping status via chat.)

• What is the desired outcome? (e.g., the AI Agent retrieves the shipping status and provides it to the customer.)

• How often is the task performed? (e.g., multiple times a day.)

Starting with manageable tasks like retrieving shipping statuses allows you to test HALO’s capabilities while minimizing complexity. This approach builds confidence and sets the stage for scaling to more complex workflows.

Step 2: Map Out Your Current Workflow

Before designing your AI Agent, map out the current process for handling the task. This will help you identify the steps your AI Agent needs to replicate or improve.

Tips for Mapping Your Workflow:

• Write each step on a separate post-it or use a digital tool like Lucidchart or Miro to create a flowchart.

• Include inputs (what triggers the step) and outputs (what happens next).

• Identify repetitive or time-consuming steps that could benefit from automation.

Example Workflow for Retrieving Shipping Status:

1. A customer asks for their shipping status via chat.

2. The agent retrieves the tracking number from the CRM.

3. The agent checks the shipping provider’s system for the status.

4. The agent provides the shipping status to the customer.

Workflows act as a "blueprint" for your AI Agent. By clearly mapping out each step, you ensure your AI Agent performs as expected and integrates seamlessly into your existing processes.

Step 3: Evaluate the Role of HALO’s AI

Not every step in your workflow requires AI. Some tasks are better handled with simple automation, while others benefit from HALO’s agentic AI capabilities.

When to Use HALO’s AI:

• For unstructured data, like interpreting customer queries or extracting information from emails.

• For decision-making, like determining the best response based on context.

• For tasks requiring integration with multiple systems, like retrieving shipping statuses from external platforms.

When to Use Simple Automation:

• For structured tasks, like copying data from one system to another.

• For straightforward actions, like sending a confirmation email.

HALO’s agentic AI is particularly powerful for tasks that require reasoning, context, or dynamic decision-making. For example, an AI Agent in HALO can retrieve shipping statuses from external systems and provide personalized updates to customers.

Examples of Workflows for AI Agents in HALO

Here are some real-world examples of tasks you can structure with workflows to design effective AI Agents in HALO:

1. Shipping Status Updates:
   Design an AI Agent that retrieves the shipping status of a package from external systems and provides the customer with real-time updates via chat, email, or phone.

2. CRM Updates:
   Create an AI Agent that extracts customer details from emails or chats and updates your CRM system automatically.

3. Feedback Categorization:
   Build an AI Agent that analyzes customer feedback from multiple channels and groups it into themes for actionable insights.

4. Product Recommendations:
   An AI Agent can analyze customer preferences and recommend products based on past purchases or browsing history.

5. Return Management:
   An AI Agent can guide customers through the return process, including generating return labels and updating inventory systems.

Tips for Getting Started with HALO

1. Start Small
   Begin with a simple use case to test HALO’s capabilities. For example, design an AI Agent to handle shipping status inquiries before expanding to more complex tasks.

2. Use Tools in HALO
   HALO provides tools to define actions and outputs for your AI Agent. Use these to structure your agent’s behavior step by step.

3. Leverage Resources
   HALO’s Knowledge Center offers tutorials, best practices, and examples of how to design effective AI Agents. These resources can help you refine your workflows and maximize HALO’s potential.

4. Iterate and Improve
   Once your AI Agent is live, gather feedback and refine its behavior. Start with a basic version and gradually add more capabilities as you gain confidence.

Common Challenges and Solutions

• Challenge: "What if my workflow is too complex?"
  Solution: Start with a smaller, simpler task and expand as you gain confidence. HALO’s tools make it easy to iterate and improve.

• Challenge: "How do I integrate HALO with my existing systems?"
  Solution: HALO supports API integrations with platforms like Shopify and Salesforce, making it easy to connect your systems.

• Challenge: "How do I monitor my AI Agent’s performance?"
  Solution: Use HALO’s monitoring tools to review conversations, analyze agent performance, and provide feedback for continuous improvement.

Conclusion

Preparation is the foundation of a successful AI Agent in HALO. By defining your use case, mapping your workflow, and evaluating HALO’s role, you’ll be ready to design an AI Agent that works seamlessly and delivers real value.

To explore these concepts further, watch the webinar below, where our AI specialists discuss practical examples, best practices, and strategies for building effective AI Agents with HALO.