Back to Templates

šŸ  Find your Home with Real Estate Agent and Bright Data

Created by

Created by: Miquel Colomer || mcolomer

Miquel Colomer

Last update

Last update 16 days ago

Share


image.png

šŸ“ Overview
This workflow transforms n8n into a smart real-estate concierge by combining an AI chat interface with Bright Data’s marketplace datasets. Users interact via chat to specify city, price, bedrooms, and bathrooms—and receive a curated list of three homes for sale, complete with images and briefings.

šŸŽ„ Workflow in Action
Want to see this workflow in action? Play the video

šŸ”‘ Key Features

  • AI-Powered Chat Trigger: Instantly start conversations using LangChain’s Chat Trigger node.
  • Contextual Memory: Retain up to 30 recent messages for coherent back-and-forth.
  • Bright Data Integration: Dynamically filter ā€œFOR_SALEā€ properties by city, price, bedrooms, and bathrooms (limit = 3).
  • Automated Snapshot Retrieval: Poll for dataset readiness and fetch full snapshot content.
  • HTML-Formatted Output: Present results as a <ul> of <li> items, embedding property images.

šŸš€ How It Works (Step-by-Step)

  1. Prerequisites:

    • n8n ≄ v1.0
    • Community nodes: install n8n-nodes-brightdata (the unverified community node)
    • API credentials: OpenAI, Bright Data
    • Webhook endpoint to receive chat messages
  2. Node Configuration:

    • Chat Trigger: Listens for incoming chat messages; shows a welcome screen.
    • Memory Buffer: Stores the last 30 messages for context.
    • OpenAI Chat Model: Uses GPT-4o-mini to interpret user intent.
    • Real Estate AI Agent: Orchestrates filtering logic, calls tools, and formats responses.
    • Bright Data ā€œFilter Datasetā€ Tool: Applies user-defined filters plus homeStatus = FOR_SALE.
    • Wait & Recover Snapshot: Polls until snapshot is ready, then fetches content.
    • Get Snapshot Content: Converts raw JSON into a structured list.
  3. Workflow Logic:

    • User sends search criteria → Agent validates inputs.
    • Agent invokes ā€œFilter Datasetā€ once all filters are present.
    • Upon dataset readiness, the snapshot is retrieved and parsed.
    • Final output rendered as a bullet list with property images.
  4. Testing & Optimization:

    • Use the built-in Execute Workflow trigger for rapid dry runs.
    • Inspect node outputs in n8n’s UI; adjust filter defaults or snapshot limits.
    • Tune OpenAI model parameters (e.g., maxIterations) for faster responses.
  5. Deployment & Monitoring:

    • Activate the main workflow and expose its webhook URL.
    • Monitor executions in the ā€œExecutionsā€ panel; set up alerts for errors.
    • Archive or duplicate workflows as needed; update credentials via credential manager.

āœ… Pre-requisites

  • Bright Data Account: API key for marketplaceDataset.
  • OpenAI Account: Access to GPT-4o-mini model.
  • n8n Version: v1.0 or later with community node support.
  • Permissions: Webhook access, credential vault read/write.

šŸ‘¤ Who Is This For?

  • Real-estate agencies and brokers seeking to automate client queries.
  • PropTech startups building conversational search tools.
  • Data analysts who want on-demand property snapshots without manual scraping.

šŸ“ˆ Benefits & Use Cases

  • Time Savings: Replace manual MLS searches with an AI-driven chat.
  • Scalability: Serve multiple clients simultaneously via webchat or embedded widget.
  • Consistency: Always report exactly three properties, ensuring concise results.
  • Engagement: Visual listings with images boost user satisfaction and conversion.

Workflow created and verified by Miquel Colomer https://www.linkedin.com/in/miquelcolomersalas/ and N8nHackers https://n8nhackers.com