# Create A Complex AI Bot which detects user intent and routes user and gives relevant answers ### Step 1: Plan User Intents and Flows * Define different user intents (e.g., sales, support, feedback, generic queries). * Map out the desired conversation flows for each intent. ### Step 2: Set Up Trigger and Initial Step * In your bot builder, set the initial trigger (e.g., user message or keyword). * Add logic or AI components that analyze the incoming message for intent. ### Step 3: Configure Intent Detection * Use the platform’s AI or intent detection feature (often NLP-based) to classify user queries. * Train or configure sample phrases for each intent to enhance accuracy. ### Step 4: Route User Based on Intent * Based on detected intent, route the conversation to the appropriate bot block or agent (e.g., sales queries to the sales bot, support to the support workflow). * For edge cases or unrecognized intents, use a fallback route with clarification prompts. ### Step 5: Connect to Trained AI or Agents * For intents needing data-driven answers, connect to relevant AI agents, ensuring they are trained with the correct documents or datasets. * Configure response mapping and fallback answers in case the AI cannot answer. ### Step 6: Implement Escalation Logic * For unresolved queries or specific intents (like complaints), add logic to escalate the chat to a human agent. * Provide users with appropriate transition messages. ### Step 7: Test and Optimize * Run multiple tests with different user queries to validate intent detection and answer routing. * Refine intent definitions, add more training examples, and optimize escalation/fallback flows. If you provide a transcript or detailed steps from the video, a more specific breakdown can be created. For now, these steps reflect the typical flow seen in the previous provided material and standard practices for AI chatbot intent detection. ## Bot Flow Template Clone Link ``` /products/bot/flow/965aa235ad380e8e0e9916461a3e9c79 ``` {% embed url="" %}