Call AI Action
Need to automate your flow even more? Try using Artificial Intelligence. Add a Large Language Model (LLM) such as OpenAI's ChatGPT or Anthropic to unlock the power of AI.
The possibilities are endless. Here are some ideas:
Auto-translate your flows into multiple languages.
Language learning: Practice conversation, translate, or quiz vocabulary.
Customer service: Handle inquiries, complaints, or refund requests conversationally.
Internal assistant: Help employees find documents, policies, or HR info.
Onboarding bot: Guide new users or team members through a process step-by-step.
Sales assistant: Qualify leads, book calls, or suggest packages.
Task automation: Integrate with APIs to handle bookings, reminders, or daily reports.
Add your LLM.
Build your flow. In the example below, we're collecting customer complaints. ChatGPT assesses how angry the customer seems and returns that to the flow where we categorize their sentiments and respond accordingly. If they're only mildly upset or annoyed, we'll open a ticket with an agent that can be responded to later on. If they're angry or very angry, we'll let the agent know they need to respond right away!
This is where you'll compose your command for your LLM. Try to be very clear!
Note that we can reference the result of this Call AI command later in the flow using @locals_llm_output like in the Split by Expression seen below.
Here, you're evaluating the numerical response you asked the LLM to give you based on the customer's input.
In this example flow, we want to escalate complaints to a human agent. We'll do that by opening a ticket. As seen in the flow editor above, we've split the sentiments into two buckets: Needs Response and URGENT. These are topics we've already created on the Tickets page. Here's how we've set up the Open Ticket action for angry and very angry customers:
We've included some details for the agent, including the text of the complaint submitted by the customer that we collected at the beginning of the flow.
Use the Simulator to give your bot a test run to see how it responds to your input. Not quite right? Tweak your request to the LLM.
Need more help? Shoot us a message via the support widget at the bottom right corner.
What Can AI Do in my Flows?
The possibilities are endless. Here are some ideas:
Auto-translate your flows into multiple languages.
Language learning: Practice conversation, translate, or quiz vocabulary.
Customer service: Handle inquiries, complaints, or refund requests conversationally.
Internal assistant: Help employees find documents, policies, or HR info.
Onboarding bot: Guide new users or team members through a process step-by-step.
Sales assistant: Qualify leads, book calls, or suggest packages.
Task automation: Integrate with APIs to handle bookings, reminders, or daily reports.
Call AI in a Flow
Add your LLM.
Build your flow. In the example below, we're collecting customer complaints. ChatGPT assesses how angry the customer seems and returns that to the flow where we categorize their sentiments and respond accordingly. If they're only mildly upset or annoyed, we'll open a ticket with an agent that can be responded to later on. If they're angry or very angry, we'll let the agent know they need to respond right away!
A Closer Look
Call AI Action
This is where you'll compose your command for your LLM. Try to be very clear!
Note that we can reference the result of this Call AI command later in the flow using @locals_llm_output like in the Split by Expression seen below.
Split by Expression
Here, you're evaluating the numerical response you asked the LLM to give you based on the customer's input.
Open Ticket
In this example flow, we want to escalate complaints to a human agent. We'll do that by opening a ticket. As seen in the flow editor above, we've split the sentiments into two buckets: Needs Response and URGENT. These are topics we've already created on the Tickets page. Here's how we've set up the Open Ticket action for angry and very angry customers:
We've included some details for the agent, including the text of the complaint submitted by the customer that we collected at the beginning of the flow.
Take your Bot for a Spin
Use the Simulator to give your bot a test run to see how it responds to your input. Not quite right? Tweak your request to the LLM.
Need more help? Shoot us a message via the support widget at the bottom right corner.
Updated on: 28/04/2025
Thank you!