AI Chatbot with Tawk Human Handoff

An AI-powered live chat support chatbot that answers customer questions using an internal knowledge base and intelligently hands off complex queries to human agents via Tawk for seamless customer support.

How the AI Flow works - AI Chatbot with Tawk Human Handoff

Flows

How the AI Flow works

Detect Chat Session Start.
Triggers when a user opens a chat session to initiate the conversation.
Display Welcome Message.
Shows a friendly greeting to the user, inviting them to ask questions.
Receive and Track User Queries.
Collects user questions and maintains chat history throughout the session.
AI-Powered Question Answering.
Uses an AI agent to search the internal knowledge base and respond to user queries.
Seamless Human Handoff via Tawk.
Forwards complex or unresolved queries to a human agent using Tawk for personalized support.

Prompts used in this flow

Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.

Welcome Message

Displays a welcome message to users when they open the chat.

                👋 Welcome to the Knowledge Base Chatbot!
I’m here to assist you by answering your questions based on our internal knowledge base 📚. If your query gets tricky, I can seamlessly forward it to a human agent using Tawk for more personalized support.

Feel free to ask me anything, and let’s get started! ✨💬
            

Tool Calling Agent System Prompt

System prompt for the LLM-powered agent that answers support questions and decides when to forward to a human agent.

                You are an AI language model assistant acting as technical live chat customer support specialist for [YOUR BUSINESS] -[DESCRIPTION OF YOUR BUSINESS] 
If conversation starts with a greeting, respond with a greeting in same language and ask how you can assist and if they have any question about our our software or it's features.
Search content relevant to question of user by connecting to DocumentRetriever. 
If you don't find any relevant evidence in context found with DocumentRetriever and ONLY IF QUESTIONS ARE RELATED TO OUR software:
- In case question was in English language, always prompt the user to connect him/her to a real agent.
- In case question in different language, first ask if visitor speaks English and be interested t be connected with English speaking support agent, and only in case of confirmation, prompt the user to connect him/her to a real agent. 
FOR UNCLEAR QUESTIONS ask for more information.

ANSWER IN THE SAME LANGUAGE as defined in Current session chat data
            

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

Chat Opened Trigger

The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

Chat History Component

The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.

Message Widget

The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.

Tool Calling Agent

Explore the Tool Calling Agent in FlowHunt—an advanced workflow component that enables AI agents to intelligently select and use external tools to answer complex queries. Perfect for building smart AI solutions that require dynamic tool usage, iterative reasoning, and integration with multiple resources.

Document Retriever

FlowHunt's Document Retriever enhances AI accuracy by connecting generative models to your own up-to-date documents and URLs, ensuring reliable and relevant answers using Retrieval-Augmented Generation (RAG).

Tawk Integration

Connect your FlowHunt AI Chatbot to Tawk for a smooth transition to human support. AI escalates chats to humans when needed, reducing errors and enhancing satisfaction.

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

Flow description

Purpose and benefits

This workflow implements a sophisticated chatbot designed to answer user questions by leveraging an internal knowledge base. When it encounters questions that are too complex or outside the scope of its knowledge, it seamlessly escalates the query to a human agent via Tawk, ensuring high-quality support at all times. The flow is designed for efficient scaling and automation, making it ideal for businesses aiming to optimize customer support processes.

Workflow Steps and Components

1. Chat Session Initiation and Welcome Message

  • Trigger: The workflow begins when a user opens a chat session.
  • Action: The chatbot automatically sends a welcoming message to the user, introducing itself and explaining its capabilities, including its ability to answer questions and escalate to a human (via Tawk) if needed.
StepComponentPurpose
Chat openedChatOpenedTriggerDetects when a new chat session starts
Welcome messageMessageWidgetSends welcome/introduction message to the user
Display messageChatOutputShows the welcome message in the chat interface

2. Capturing User Input and Chat History

  • User Input: The user enters their question or message into the chat.
  • Chat History: The workflow maintains a real-time history of chat exchanges, ensuring full context is available for accurate responses and escalation if needed.
StepComponentPurpose
Capture inputChatInputReceives user’s message
Store historyChatHistoryKeeps track of conversation context

3. Automated Response with Knowledge Base Integration

  • Knowledge Retrieval: When a user submits a question, the chatbot (Tool Calling Agent) queries an internal Document Retriever to search for relevant information within the organization’s knowledge base.
  • Response Generation: The AI uses retrieved knowledge to compose a helpful answer. If the context is insufficient or the question is unclear, the bot asks the user for more information.
StepComponentPurpose
Retrieve docsDocumentRetrieverSearches internal knowledge base for relevant content
Generate answerToolCallingAgentUses AI to respond or decide if escalation is needed

4. Intelligent Escalation to Human Support (Tawk Integration)

  • Escalation Logic:
    • If the user’s query cannot be answered based on the knowledge base, and the question is about the software, the chatbot considers language:
      • If in English: suggests connecting to a real human agent.
      • If in another language: asks if the user would like to be connected to an English-speaking support agent.
  • Seamless Handover: The chatbot provides a button or prompt (using TawkHumanAssistTool) for the user to connect with a human agent via Tawk, optionally including relevant chat history to assist the human operator.
  • Display: The outcome (AI answer or escalation prompt) is shown in the chat.
StepComponentPurpose
Human handoverTawkHumanAssistToolEnables contacting a human agent via Tawk
Show responseChatOutputDisplays AI or escalation message to the user

Key Features and Advantages

  • Automated First-Line Support: Handles the majority of routine and knowledge-based queries automatically, reducing the workload for human agents.
  • Contextual Understanding: Maintains chat history and leverages internal documentation for precise responses.
  • Intelligent Escalation: Ensures users are not left frustrated by AI limitations—complex or ambiguous issues are routed to humans.
  • Multi-Language Handling: The chatbot can respond in the user’s language, and intelligently handles handover for non-English users.
  • Enhanced User Experience: Users receive fast, helpful answers and clear guidance if escalation is necessary.

Why This Workflow is Useful for Scaling and Automation

  • Scalability: Can handle multiple chats simultaneously without increasing human resource requirements.
  • Consistency: Provides standardized, accurate answers based on the latest internal knowledge.
  • Efficiency: Reduces response times and ensures human agents only handle queries that truly require their expertise.
  • Customer Satisfaction: Ensures users always have a path to personalized support if needed, preventing dead ends.

This workflow is ideal for businesses looking to automate frontline support, maximize agent productivity, and maintain high-quality customer interactions at scale.

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