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Real estate chatbot with AI property matching and automated calendar scheduling

GenziGenzi
2571 views
2/3/2026
Google SheetsZoho CRMAutomationCRM IntegrationData Sync
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Description

A comprehensive real estate chatbot automation system that handles customer inquiries, property searches, and appointment scheduling through intelligent conversation flows and email processing.

How it works?

This template creates an end-to-end real estate automation system that handles customer inquiries from initial contact through appointment booking.

1. Customer Entry Point

  • Webhook receives customer messages from chat interface
  • Link detection checks if customer shared property URLs
  • Smart routing - if property link found, fetch details immediately; otherwise proceed to chat

2. AI Content Processing

  • Content filter (PRIORITY) - blocks non-real estate queries upfront
  • Information extraction - scans messages for personal details and property requirements
  • Human handoff detection - identifies requests for live agent assistance

3. Data Collection Phase

  • Sequential gathering: Personal info (name → phone → email) then property needs
  • Smart validation - phone format, email structure, budget parsing
  • No redundancy - never asks for information already provided
  • PostgreSQL storage - saves customer data and conversation memory

4. Property Search & Matching

  • Database query filters properties by type, location, budget, availability
  • Image enhancement - fetches property photos from media storage
  • Results ranking - returns top 5 matches sorted by price

5. AI Response Generation

  • GPT-4 formatting creates engaging, professional property listings
  • Visual enhancement - includes property images and key details
  • Personalized tone - acknowledges customer preferences

6. Appointment Automation

  • Gmail monitoring - checks for appointment confirmations every hour
  • Calendar integration - creates, updates, deletes appointments automatically
  • Smart scheduling - checks availability, suggests alternatives for conflicts
  • Email responses - sends confirmations and follow-ups

Intelligence Features

Context Awareness
  • Remembers conversation history across sessions Builds complete customer profile progressively Maintains property preferences throughout interaction
Smart Extraction
  • Recognizes property types: HDB, Condo, Apartment
  • Parses locations and MRT preferences automatically Handles various budget formats (SGD 2,500, $2500, etc.) Identifies timeline requirements and citizenship status

Professional Handoffs

  • Detects human agent requests with keyword matching
  • Collects complete customer context before transfer
  • Sends structured handoff emails with all requirements
  • Ensures smooth transition to live agents

Technical Components

AI Models
  • OpenAI GPT-4 - Main conversation handling and response formatting
  • GPT-4 Mini - Appointment processing and email management
  • LangChain Memory - Conversation context retention

Database Integration

  • PostgreSQL - Customer data, property listings, conversation history
  • Property search with multi-criteria filtering Media storage integration for property images

Communication Channels

  • Webhook API - Primary chat interface
  • Gmail integration - Appointment confirmations and notifications
  • Google Calendar - Automated scheduling and availability checking

Setup Requirements

  • Configure database - PostgreSQL with property and customer tables
  • Set up integrations - Gmail, Google Calendar, OpenAI API
  • Customize prompts - Adjust AI responses for your brand
  • Test workflow - Verify end-to-end functionality
  • Monitor performance - Track conversation success rates
  • The system is designed to handle the complete customer journey from initial inquiry to scheduled property viewing, with intelligent automation reducing manual work while maintaining high service quality.

n8n Workflow: AI-Powered Chatbot with Property Matching and Calendar Scheduling

This n8n workflow creates an AI-powered chatbot that can respond to user queries, perform property matching using a search tool, and manage chat history using a PostgreSQL database. It's designed to automate interactions, provide relevant information, and maintain context in conversations.

What it does

This workflow automates the following steps:

  1. Receives Incoming Requests: It listens for incoming HTTP requests (e.g., from a chatbot frontend or other applications) via a Webhook.
  2. Initializes AI Agent: It passes the incoming user message to an AI Agent configured with an OpenAI Chat Model.
  3. Manages Chat History (PostgreSQL): The AI Agent utilizes a PostgreSQL database for chat memory, allowing it to maintain context across conversations.
  4. Performs Property Search (SerpAPI): The AI Agent is equipped with a SerpAPI (Google Search) tool, enabling it to search for real-time property information or other relevant data based on user queries.
  5. Processes AI Agent Response: The response from the AI Agent, which could be a direct answer or an indication of an action taken (like a property search), is captured.
  6. Conditional Logic for Email Trigger: It includes an "If" node, suggesting a conditional branch. Although not fully connected in the provided JSON, this node is typically used to trigger different actions based on the AI's response (e.g., if the AI determines a calendar scheduling is needed or an email should be sent).
  7. Sends Email (Gmail Trigger - Unconnected): A Gmail Trigger node is present but not connected to the main flow. This suggests a potential future or alternative use case where the workflow could be triggered by or send emails based on the AI's output.
  8. Responds to Webhook: Finally, it sends the AI's response back to the original caller via the Webhook, completing the request-response cycle.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • OpenAI API Key: For the OpenAI Chat Model to process natural language.
  • SerpAPI API Key: For the SerpAPI (Google Search) tool to perform real-time searches.
  • PostgreSQL Database: A PostgreSQL database instance to store chat memory. You will need the connection details (host, port, user, password, database name).
  • Gmail Account (Optional): If you intend to activate the Gmail Trigger functionality.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • OpenAI Chat Model: Set up your OpenAI API credentials.
    • SerpAPI: Set up your SerpAPI credentials.
    • Postgres Chat Memory: Configure your PostgreSQL database credentials.
  3. Activate the Webhook: The "Webhook" node will provide a unique URL. This URL is where your chatbot frontend or other applications should send user messages.
  4. Configure AI Agent: Review and adjust the "AI Agent" node's settings, including its system message, tools, and memory configuration, to fine-tune its behavior for property matching and scheduling.
  5. Test the Workflow: Use the "Test Workflow" feature in n8n or send a sample request to the Webhook URL to ensure everything is working as expected.
  6. Connect Conditional Logic (Optional): If you want to enable specific actions based on the AI's response (e.g., calendar scheduling), connect the "If" node to relevant subsequent nodes (e.g., a calendar scheduling node, which is not included in this JSON but implied by the directory name).

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