Conversational Flow Overview
The SigmaMind AI platform provides an AI agent builder that allows users to design custom conversational AI agents by connecting various nodes and modules.
1. Configure the Start Trigger
The “Start Trigger” is the initial component that determines how your AI agent flow is activated.
- Default Trigger: When you add a new AI agent, the “Start Trigger” is included by default.
- Multiple Triggers: You can add more than one trigger event if you want the same flow to work across multiple channels, such as voice, chat, and email.
- Filter by Intent: To make the agent trigger only for specific customer requests, you can filter by intent. For example, if you select “schedule an appointment” as an intent, the AI agent will only activate when an inbound request is about scheduling an appointment. Otherwise, the flow won’t trigger, and the request might be handled by a human agent or another setup. You can also specify multiple intents.
2. Define Send Responses
The “Send Response” module allows your AI agent to communicate with the customer.
- Drag and Drop: You can drag and drop this node into your flow.
- Response Types:
- Prompt: You can provide a direct prompt as a response, breaking your flow into smaller conversational segments, such as greeting a customer.
- Templates/Macros: If you have pre-built templates or macros, you can select the
static category
to use them as responses.
- Channel-Specific Responses: You can customize responses based on the channel. For instance, a phone voice conversation might have a different prompt than an email, by selecting the appropriate channel within the module.
4. Detect User Intent
The “User Intent” module helps the AI agent understand what the customer is saying.
- Mini-Prompts: This module is essentially a mini-prompt designed to detect the customer’s intent.
- If-Then-Else Conditions: You can set up one or multiple “if-then-else” conditions. For example, if the customer’s message is about “canceling an order,” the flow can be directed to a specific app action or a different response. This allows you to break down the conversation into multiple prompts based on detected customer intent.
3. Implement Wait Conditions
The “Wait” module enables the AI agent to pause and wait for customer input or an intentional delay.
- Drag and Drop: Add this module to your flow by dragging and dropping it.
- Event-Based Waiting: You can set an event for which the agent should wait. For example, selecting
ticket message created customer
will make the agent wait for a customer’s reply in the conversation flow. This is crucial for back-and-forth conversations, such as after an agent greets a caller and expects a response. - Conditions: You can add specific conditions for each waiting event.
- Intentional Delay: You can set a delay, such as a 24-hour or 8-hour window, if you need to wait for a customer message within a specific timeframe. This helps set up conversational automation.
5. Integrate with Third-Party Systems via App Actions
The “App Action” module is where all third-party API integrations come into play, allowing the AI agent to retrieve information or take actions in external systems.
- API Integrations: If you have set up API integrations (e.g., with Shopify or a CRM system), they will appear in a dropdown.
- Available Requests: The dropdown will show all available API requests for the selected application, such as a
get order request
for Shopify or fetching/posting customer info in a CRM. - Retrieve Information/Take Action: This module allows you to retrieve specific information (e.g., order details) or take actions (e.g., posting info) related to a customer.
Adding and Managing Apps
Before using “App Actions,” you need to set up your integrations in the “Apps” section.
- Add Applications: Go to the “Apps” section to add all your third-party integrations.
- Define API Actions: For each integrated app, you can add specific API actions (e.g.,
get request
for retrieving order info from Shopify). - Configure Variables and API Keys: Within this section, you can set up variables and add API keys for your integrations.
6. Create Conditional Paths with Branching
The “Branch” module enables you to add pre-validations and multiple conditions to guide the conversation flow.
- Multiple Conditions: You can think of “Branch” as a way to perform checks before deciding the direction of the conversation.
- AND/OR Conditions: You can combine multiple conditions using “and” or “or” logic.
- Integration Fields: This module pulls fields directly from your API integrations (e.g., “Shopify order status”). You can then select different conditions based on these fields.
- Connecting Modules: Based on these pre-validations, you can connect the “Branch” module to various other modules, allowing for dynamic conversation paths.
7. Design an Overall Flow (Example: Looping Responses)
Modules can be arranged and connected to create complex conversational flows. A common pattern involves looping responses back to the “Wait” module to continue the conversation.
- Example: Cancel Order Request:
- The customer places a cancel order request.
- “User Intent” messages detect the request, and “App Actions” retrieve specific order information (e.g., looking up email ID or phone number).
- After the AI agent responds (e.g., offering a 30% discount instead of cancellation), the flow can loop back to the “Wait” module.
- This forces the agent to wait for the customer’s response to the AI’s offer, allowing for a continuous conversation. You can have multiple such loops.
8. Test Your AI Flow in the Playground
Once you have built your AI flow, you can test it directly within the SigmaMind AI platform.
- Access Playground: Navigate to the “Playground” section from the menu.
- Simulate Input: You can simulate an inbound request by adding a subject, a random email ID, selecting a channel from a list, and typing a message, then hitting submit.
- View Events: The playground will show if your AI agent’s triggers are met and if the flow is activated. You can then view the events and steps to verify that everything happened as expected.