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

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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.