How to Test and Fix Voice AI Agent Prompts with Twilio Conversation Relay and Cekura

A Twilio tutorial demonstrates how to build, test, and improve a voice AI banking assistant using Conversation Relay, Node.js, OpenAI, ngrok, and Cekura. Conversation Relay manages real-time speech recognition, synthesis, interruptions, and turn-taking, while the application controls prompts, business logic, and account-related tools such as account lookup and debit-card replacement. The guide connects Cekura to a WebSocket test endpoint, defines deterministic Python and AI-judged metrics, generates simulated customer conversations, and evaluates whether the agent follows required workflows and policies. Initial tests expose prompt gaps that cause the assistant to incorrectly waive replacement-card fees for Premium accounts and omit referrals to the fraud team for unauthorized charges. After refining the system prompt to explicitly define eligibility, ordering rules, and fraud limitations, the example’s pass rate rises from 8 percent to 92 percent, though testing also identifies an unresolved edge case involving disputed mailing addresses. The tutorial presents prompts as versioned, testable software artifacts and recommends repeated automated testing, evaluator refinement, and eventual real voice-call testing before deployment.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.