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Answer real estate questions with AI using PropertyFinder.ae, OpenRouter, and SerpAPI

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Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

AI Real Estate Agent with OpenRouter and SrpAPI to talk with property objects from propertyfinder.ae This n8n template demonstrates a simple AI Agent that can: Scrape information from a provided li...

Best for

  • Support Chatbot automation workflows
  • AI Chatbot automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.code, n8n-nodes-base.httprequest, n8n-nodes-base.merge, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.lmchatopenrouter, @n8n/n8n-nodes-langchain.toolserpapi

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by George Zargaryan.

Original n8n.io source

1.1 Workflow description

Title
Answer real estate questions with AI using PropertyFinder.ae, OpenRouter, and SerpAPI
Workflow name
Answer real estate questions with AI using PropertyFinder.ae, OpenRouter, and SerpAPI

AI Real Estate Agent with OpenRouter and SrpAPI to talk with property objects from propertyfinder.ae

This n8n template demonstrates a simple AI Agent that can:

  • Scrape information from a provided propertyfinder.ae listing link.
  • Answer questions about a specific property using the scraped information.
  • Use SerpAPI to find details that are missing from the scraped data.
  • Answer general real-estate questions using SerpAPI.

Use Case

This workflow serves as a starting point for building complex AI assistants for real estate or other domains.

See the demo video

Potential Enhancements

  • Expand Knowledge: Augment the workflow with your own knowledge base using a vector database (RAG approach).
  • Add More Sources: Adapt the scraper to support other real estate websites.
  • Optimize Speed: Add a cache for scraped data to reduce response latency.
  • Improve Context Handling: Implement reliable persistence to track the current listing instead of iterating through conversation history.
  • Customize Prompts: Write more tailored prompts for your specific needs (the current one is for demonstration only).
  • Integrate Channels: Connect the workflow to communication channels like Instagram, Telegram, or WhatsApp.

How It Works

  1. The workflow is triggered by a "When chat message received" node for simple demonstration.
  2. The Chat Memory Manager node extracts the last 30 messages for the current session.
  3. A code node finds the property link, first by checking the most recent user message and then by searching the conversation history.
  4. If a link is found, an HTTP Request node scrapes the HTML content from the listing page.
  5. The Summarize code node parses the HTML, retrieves key information, and passes it to the AI Agent as a temporary knowledge base.
  6. The final AI Agent node answers user queries using the scraped knowledge base and falls back to the SerpAPI tool when information is missing.

How to Use

  • You can test this workflow directly in n8n or integrate it into any social media channel or your website.
  • The AI Agent node is configured to use OpenRouter. Add your OpenRouter credentials, or replace the node with your preferred LLM provider.
  • Add your SerpAPI key to the SerpAPI tool within the AI Agent node.

Requirements

  • An API key for OpenRouter (or credentials for your preferred LLM provider).
  • A SerpAPI key. You can get one from their website; a free plan is available for testing.

Need Help Building Something More?

Contact me on:

Happy Hacking! πŸš€

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Find link

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 2 - Scrape

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 3 - Summarize

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 4 - Merge

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 5 - Capture Incoming Message

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 6 - Capture

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 7 - AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Block 8 - Simple Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 9 - OpenRouter Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices
Version 1

Block 10 - SerpAPI

Type / Role
@n8n/n8n-nodes-langchain.toolSerpApi - toolSerpApi
Config choices
Version 1

Block 11 - If msg contains link

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.2

Block 12 - Chat Memory Manager

Type / Role
@n8n/n8n-nodes-langchain.memoryManager - memoryManager
Config choices
Version 1.1

Block 13 - Simple Memory1

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 14 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 15 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 16 - Chat input

Type / Role
@n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices
Version 1.3

Block 17 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 18 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

3. Summary Table

Workflow Answer real estate questions with AI using PropertyFinder.ae, OpenRouter, and SerpAPI
Complexity advanced
Nodes 18
Categories Support Chatbot, AI Chatbot
Author George Zargaryan
Published 05 Sept 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/8309/8309.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Answer real estate questions with AI using PropertyFinder.ae, OpenRouter, and SerpAPI do?

AI Real Estate Agent with OpenRouter and SrpAPI to talk with property objects from propertyfinder.ae This n8n template demonstrates a simple AI Agent that can: Scrape information from a provided li...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.