💬 🏠 Find your home with Real Estate Agent and Bright Data

⚡ 3,429 views · 💬 Lead Nurturing & AI Sales Agents

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Description

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📝 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.

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

🔑 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 “FOR_SALE” 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.

🚀 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 “Filter Dataset” 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 “Filter Dataset” 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 “Executions” panel; set up alerts for errors.
   • Archive or duplicate workflows as needed; update credentials via credential manager.

✅ 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.

👤 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.

📈 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

🔗 Nodes Used

Execute Workflow Trigger, AI Agent, OpenAI Chat Model, Simple Memory, Call n8n Workflow Tool, Chat Trigger

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup