Real estate
with AISpend less time finding property information
An enquiry can send a broker back through listing sheets, property records and management emails. Before a viewing, the team gathers preferences; afterwards, it updates the CRM. Finding and checking information adds work around every customer conversation.
Start with one reviewable task, such as drafting replies from approved property records or preparing a viewing comparison. Sales brokerage, rental brokerage and property management need different data and update routines.
Two directions illustrated by published industry examples
Mitsui Fudosan Realty announced its Rehouse AI Chat beta on January 13, 2026. It answers questions using information on property detail pages, illustrating assistance tied to a specific listing.
In an August 25, 2025 article, JLL Japan describes generating document drafts from materials such as emails and stresses expert review. This illustrates internal document preparation.
The workflows below are our own design proposals informed by these examples. They are not deployments of those companies’ products or promises of equivalent results.
Choose the first workflow
Use enquiry volume, repetitive entry and time spent finding documents to set priorities. Keep public-facing answers separate from assistance using internal records.
| Workflow | AI prepares | People confirm |
|---|---|---|
| Initial enquiries | Draft replies grounded in approved listing data and questions about preferences | Availability, charges and the final response |
| Comparisons and viewings | Differences between properties and missing information | Properties to offer, current availability and viewing times |
| Document preparation | Extracted fields, drafts and conflicting source values | Original records, contract terms and specialist judgments |
| Tenant and owner requests | Request summaries and handoff notes | Urgency, contractor arrangements, cost responsibility and replies |
Prepare data and connections
Begin with authorised documents or exports. Check available APIs before expanding integration; replacing every existing system is not a prerequisite.
| Source | What to check |
|---|---|
| Property records and listing sheets | Property and unit IDs, update times, status, rent and management fees |
| CRM and enquiry emails | Customer ID, preferences, contact history and staff access |
| Building rules, equipment records and FAQs | Document version, applicable property, public information and exception contacts |
| Viewing calendars and activity records | Confirmation process, duplicate prevention and notifications |
From enquiry to viewing preparation
This example keeps a rental agent responsible for approving and sending each reply.
| Step | AI and system | Human review |
|---|---|---|
| 1. Receive | Link the enquiry to a property ID and organise preferences | Confirm the property and customer |
| 2. Check sources | Read records and FAQs; show source versions and timestamps | Resolve stale terms and conflicting records |
| 3. Draft | Separate supported answers from questions for the property manager | Confirm current terms and send the response |
| 4. Prepare | Create a comparison and viewing brief from the conversation | Agree a time with the customer and confirm the booking |
Example output: a property confirmation note
The following uses fictional properties and enquiries. It is not a live listing or output from an operating customer system.
| Question | Draft or action | Source and status |
|---|---|---|
| Monthly charges | JPY 120,000 rent plus JPY 10,000 management fee; other charges to confirm | Specified version of property A record; calculate totals deterministically |
| Pets | No statement in the listing sheet; ask the manager | Do not infer that pets are allowed |
| Move-in date | Record and listing page disagree; confirmation required | Attach both values and their update times |
| Next action | Check availability, then arrange a viewing around customer preferences | A person confirms; do not claim an unconfirmed booking |
Keep replies grounded and reviewable
Show retrieval times for availability and prices. Route stale, ambiguous or conflicting information for review. Keep sources and corrections with the draft.
Do not expose internal-only information in customer replies. Staff and qualified specialists retain contract and disclosure responsibilities; AI supports preparation. Provide a defined escalation route for urgent property issues.
Measure a narrow pilot
A possible starting point is one team and approximately 20 authorised past enquiries, producing drafts for staff review. This is an illustrative trial size. Check source updates and handoffs before considering customer-facing automation.
Compare similar cases before and during the pilot, including review and correction time. Track viewing and transaction outcomes separately rather than inferring revenue gains from faster replies.
| Measure | What to record |
|---|---|
| Handling time | Search, drafting, review and correction combined |
| Accuracy | Stale terms, wrong-property records and unsupported answers |
| Handoff reliability | Missed pending checks, delays and duplicate handling |
| Cost and business outcomes | Usage cost and review effort per case; viewing and transaction outcomes separately |
Examples and checks for specific workflows
Choose a workflow to explore inputs, examples, and human review in more detail.
Explore by workflow
Each guide includes an editable text worksheet.
Discuss a starting point with Atlas Support
Tell us whether the focus is brokerage or management, which property and CRM systems you use, monthly enquiry volume and the task that takes the most time. Initial enquiries do not require customer personal data or original contracts.
We can scope workflow design, source permissions, review screens, integrations, a prototype and evaluation. Cost and timing depend on source quality, integrations and scope.
Explore AI for your property operations
Choose a starting point: enquiries, property records, viewing preparation or management requests.