BackReal Estate · Case Study

AI Assistant for 4 Brokerages

12hr
Saved Per Agent Per Week

The Client

A regional real estate group running four brokerages with 180+ agents across MLS systems, a shared CRM, and brokerage-level accounting.

The Challenge

Agents constantly pinged office admins with the same questions: commission splits, listing status, MLS rules, comp pulls, and contract clauses. Admins spent most of the day answering Slack messages instead of supporting closings.

What We Built

Built a unified AI assistant trained on every brokerage's policy docs, contract templates, and commission structures.

Connected the assistant to MLS data, the shared CRM, and accounting so it can answer questions with live, cited sources.

Deployed it inside Slack and as a branded web app, with single sign-on so agents only see what they're allowed to see.

Added weekly review cycles where unanswered questions become new knowledge base entries.

Stack
Claude 3.5 SonnetSupabase + pgvectorMLS APIsSlackCustom RAG pipeline
Results
12hr
Saved per agent per week
87%
Questions answered without a human
Faster onboarding for new agents

Our admins finally get to focus on closings instead of answering the same five questions all day.

Managing Broker

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