Augment Voice Calls with Twilio Conversation Intelligence Using Node.js

This Node.js tutorial explains how to enhance an existing Twilio Conversation Relay voice agent, such as the Owl Air example, with Twilio Conversation Intelligence, Conversation Orchestrator, and Conversation Memory to analyze calls after they end. It guides developers through creating a Conversation Configuration and Memory Store, configuring an Intelligence rule that generates call summaries, caller sentiment analysis, and script-adherence results, and delivering those results to a public webhook endpoint through ngrok. The application adds an Express POST route that parses Twilio’s webhook data, queries the Conversations API for call timestamps, and stores call records, operator results, and script-adherence categories in a SQLite database. The implementation uses classes to model summaries, sentiment, adherence data, and categories, a database service with prepared statements and transactions for reliable persistence, and a Twilio REST client authenticated through environment variables. After starting the application and testing calls, developers can inspect stored results and potentially extend the project with routes for viewing conversation summaries and individual call details.

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