Build a real-estate ops assistant in n8n
They wired an n8n agent to manage chats, property updates, and scheduling with memory and calendar automation.
- What they did
- They set up an n8n workflow as an operations helper for a real-estate business. Incoming client messages go to an AI agent that can keep context across conversations, while long-term information is saved with vector embeddings in Supabase. The workflow can refresh property details, verify availability, and handle appointments through Google Calendar, then send replies and notices through Gmail. They also built the logic so the calendar piece can be swapped for a client’s preferred tool.
- How it went
- The system was used for conversations, lead qualification, follow-up, scheduling, and property updates in one place. They said Google Calendar booking, rescheduling, and cancellations worked smoothly. No hard usage numbers or deployment stats were given.
- Tips
- If you need memory, separate short-term chat context from long-term stored knowledge. For any workflow that changes records or sends messages, add a review step before the action runs.
Try it yourself with n8n
Create an n8n workflow for my [real-estate business] that handles incoming messages from [clients/tenants/leads], answers using data from [property database/spreadsheet], and remembers prior context for each person. Store longer-term knowledge in [Supabase/vector embeddings or similar], update fields like [availability, price, status] when appropriate, and use [Google Calendar or another booking tool] to book, reschedule, or cancel appointments. Before you change any record, send any message, or make any calendar action, show me the exact plan and wait for my approval. Then run a test conversation for [one property] and stop after confirming the full flow works.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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