Setup checklist for a real estate AI receptionist
A complete checklist for deploying the 365agents Residential Agent — MLS feed integration, team roster setup, neighborhood knowledge base, showing rules, and fair housing-aware configuration.
Written By Rick Garcia
Last updated 15 days ago
Deploying an AI receptionist for a real estate team takes about a week of elapsed time, with the bulk of the work going into MLS integration, team roster configuration, and building out neighborhood knowledge that makes the AI sound like a local expert.
Before the kickoff call
- CRM / platform — Follow Up Boss, Chime, kvCORE, BoomTown, Real Geeks, LionDesk, Top Producer, or similar (with admin credentials)
- MLS access — MLS login or IDX feed credentials for real-time listing data
- Team roster — agents, their specialties (buyer / seller / both, luxury / first-time / investor), territories, calendars
- Listing portfolio — current active listings and their key details
- Service area — zip codes, neighborhoods, cities you serve
- Neighborhood knowledge base — for each major neighborhood: school district, commute, typical price range, key amenities, HOA communities
- Showing rules — showing windows per agent, drive-time preferences, lockbox/key access methods
- Qualification criteria — what makes a "motivated" buyer in your market (pre-approved, specific timeline, etc.)
- Seller lead routing — which agent or listing coordinator gets seller leads
- Top 20–30 FAQs
Decisions you'll need to make
- Voice — Nova (warm, enthusiastic, knowledgeable) is our default for real estate
- Disclosure — we recommend proactive disclosure
- After-hours coverage — AI all hours including evening / weekend (when most real estate calls actually come in)
- Seller lead handling — direct transfer to a listing agent, or appointment booking, or both depending on time
- Buyer qualification depth — how many questions to ask before transferring vs. book appointment for agent to qualify
- Fair housing guardrails — explicit list of topics the AI should not characterize (demographics of neighborhoods, typical buyers, etc.)
- Rental inquiry handling — do you service rentals, or decline / refer
MLS / IDX integration
- Authorize IDX feed access for real-time listing data
- Confirm listing data refresh frequency (ideally every 15 minutes or better)
- Map MLS fields to the AI's listing-answer templates
- Set up listing-agent assignment (so the AI books showings on the correct person)
- Configure coming-soon, pending, and sold status handling
Fair housing considerations
- The AI should never characterize the demographics of a neighborhood
- The AI should not steer callers based on protected characteristics
- Neighborhood answers should be factual (schools, commute, amenities) — not opinion-based ("family-friendly," "up-and-coming," etc. depending on context)
- Your team should review the AI's standard neighborhood responses with an eye toward fair housing compliance before go-live
- The AI can recommend specific agents for specific territories but should not imply demographic preferences
Team roster configuration
- For each agent: name, territories, specialties, showing availability, seller-vs-buyer split
- Calendar integration for each agent (Google or Outlook)
- Round-robin rules for new buyer leads if no specific territory match
- Escalation path when the assigned agent is unavailable
Neighborhood knowledge base
- One-page factsheet per major neighborhood you serve
- School district info (factual — district name, elementary/middle/high school names)
- Commute info (time to downtown, nearest highway access)
- Price range (MLS-derived median/range, not opinions)
- HOA info for communities with HOAs
- Key factual amenities (parks, shopping, transit)
Call forwarding
- Current phone system — setup guides in our Call forwarding collection
- Forwarding rules — always, after-hours, overflow
- Urgent escalation for motivated buyers — direct line or SMS + call
Go-live sequence
- Day 1: kickoff, requirements, MLS integration, team roster setup
- Day 2–3: neighborhood knowledge base loaded, showing rules configured
- Day 3–5: internal test calls, listing scenario testing
- Day 5–7: soft launch (after-hours first), full rollout
- Weeks 2–4: refinement based on real call patterns; MLS listing updates tested
What to measure after go-live
- Speed-to-lead — time from first inquiry to first agent contact
- Showing booking rate
- Motivated buyer capture
- Seller lead capture
- Fair housing review — sample transcripts to confirm neighborhood answers stay factual
- Lead qualification accuracy
Related articles
- How 365agents works for real estate teams
- Common calls a real estate AI handles
- Can AI really book appointments?
Start the process
Book a demo and our team will walk through this checklist, configure a live Residential Agent against your MLS feed, and give you a clear go-live plan.