Payment AI Agent Scripted for Webex Contact Center (Contact Center)

Payment AI Agent Scripted for Webex Contact Center

Playbook by Webex for Developers

Payment AI Agent Scripted for Webex Contact Center

Deploy a scripted payment AI agent for balance lookup and payment processing in Webex Contact Center

Deploy a scripted payment AI agent for balance lookup and payment processing in Webex Contact Center
View Playbook
Playbook by Webex for Developers

A Webex Contact Center scripted-agent sample that connects AI Agent Studio and Flow Designer for inbound payment self-service: balance lookup, payment detail collection, subflow fulfillment, and caller-facing payment confirmation.

Why use this playbook

  • Ship faster: Start from importable AI Agent Studio and Flow Designer exports instead of building the state-event pattern from a blank flow.
  • Fewer event-mapping mistakes: Shows the exact custom events, variables, and subflow handoffs used for balance and payment paths.
  • Endpoint-ready pattern: Uses explicit endpoint placeholders so teams can connect approved balance and payment services before testing.
  • Safer review path: Calls out sample IDs, endpoint placeholders, and sensitive payment data handling before a team adapts the flow for a real environment.

What it does

  • Imports a scripted Payment_Agent_Scripted AI Agent with balance, payment, and payment-detail collection intents.
  • Imports a main Payment_Flow_Scripted voice flow that routes AI Agent custom state events through Flow Designer.
  • Calls checkBalance and makePayment subflows, then sends announceBalanceResponse and paymentResultResponse state events back to the AI Agent.
Support

Third-Party Tool

Estimated Implementation Time

2-4 hours

Categories

A Webex Contact Center scripted-agent sample that connects AI Agent Studio and Flow Designer for inbound payment self-service: balance lookup, payment detail collection, subflow fulfillment, and caller-facing payment confirmation.

Why use this playbook

  • Ship faster: Start from importable AI Agent Studio and Flow Designer exports instead of building the state-event pattern from a blank flow.
  • Fewer event-mapping mistakes: Shows the exact custom events, variables, and subflow handoffs used for balance and payment paths.
  • Endpoint-ready pattern: Uses explicit endpoint placeholders so teams can connect approved balance and payment services before testing.
  • Safer review path: Calls out sample IDs, endpoint placeholders, and sensitive payment data handling before a team adapts the flow for a real environment.

What it does

  • Imports a scripted Payment_Agent_Scripted AI Agent with balance, payment, and payment-detail collection intents.
  • Imports a main Payment_Flow_Scripted voice flow that routes AI Agent custom state events through Flow Designer.
  • Calls checkBalance and makePayment subflows, then sends announceBalanceResponse and paymentResultResponse state events back to the AI Agent.