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In this comprehensive tutorial for developers and technical professionals, we walk you through building an end-to-end digital AI Agent for insurance using Cognigy.AI. This Agent will help customers with claims, invoices, and frequently asked questions, all while automating workflows and enhancing customer engagement via chat. What you'll learn: End-to-End AI Agent Design: Build an insurance AI Agent that covers key functionalities such as FAQs, intent handling, and greeting patterns. Use Case Overview: Learn how to structure an agent capable of addressing customer claims, invoices, and general queries. Adding Intents and Routing Conversations: Implement intents and ensure seamless conversation flow, directing customer interactions based on detected intents. Knowledge AI: Discover how to leverage Cognigy.AI’s Knowledge AI to enable your agent to dynamically access and respond to knowledge-based queries. Set up fallback mechanisms using Cognigy’s Knowledge AI to handle missed or unrecognized intents. Authentication Flow Creation: Design a secure authentication process to verify customer identity. Transaction Flow with LLM Support: Build a transaction flow for handling claims, utilizing question nodes and LLM-based re-prompts to guide customers. Deploying to a Channel: Finally, deploy your agent to a channel, enabling real-time interactions with users. Whether you're an experienced developer or a solution architect, this detailed tutorial equips you with the tools and best practices for building intelligent, AI-powered insurance solutions using Cognigy.AI. Get ready to take your conversational AI expertise to the next level! ============= 00:00 Intro 01:37 Creating the Project 05:09 Setting-up LLMs 08:09 Setting-up the NLU 13:07 Setting-up Knowledge AI 29:40 Deploying to Webchat 41:33 Setting up the Authentication Flow 49:38 Advanced Debugging