AI Agent
Overview
Developed a context-aware conversational agent deployed across WhatsApp, Telegram and Web. It uses RAG (Retrieval-Augmented Generation) to answer business-specific questions and execute tasks like booking appointments autonomously.
System Architecture
LOG_FLOW_v2.0Intent Recognition
Incoming messages are parsed using LLMs to identify user intent and extract key entities (dates, names, services).
Knowledge Retrieval
The system queries a Vector Database (RAG) to pull relevant business documentation, ensuring the AI never 'hallucinates' facts.
Context Management
Maintains a sliding-window memory of the conversation to handle multi-turn dialogues and follow-up questions naturally.
Action Triggering
If the user intent requires action (like booking), the bot triggers external APIs to update calendars or CRMs in real-time.
Sentiment Routing
Monitors user frustration levels; if sentiment drops below a threshold, the bot automatically handshakes the chat to a human agent.