AI-Powered Listing Assistant for a Multi-Agent Real Estate Brokerage

Overview

Built a conversational AI assistant embedded directly on the brokerage's listing pages to answer buyer questions about square footage, HOA fees, school zones, and showing availability in real time. The assistant was trained on each listing's data feed so answers stayed accurate as properties came on and off market, and it handed off warm leads to the right agent with full conversation context attached. Previously, agents were fielding the same repetitive questions by phone during evenings and weekends, pulling their attention away from active negotiations. The rollout also included a lightweight agent dashboard for reviewing assistant conversations and adjusting canned responses without engineering support. Agents were fielding repetitive buyer questions — square footage, HOA fees, school zones, showing availability — by phone during evenings and weekends, pulling their attention away from active negotiations. Response times outside business hours were inconsistent, and some inquiries went unanswered until the next day. We built a conversational AI assistant trained directly on the brokerage's live listing feed and embedded it on every listing page, so it could answer common buyer questions accurately and hand off qualified leads to the right agent with full context attached. We began with a two-week discovery phase mapping the brokerage's most common buyer questions and listing data structure, then built and trained the assistant against a staging feed before piloting it on a subset of listings. After a feedback loop with agents, we rolled it out brokerage-wide and handed over the dashboard with a short training session. The assistant now handles the majority of routine buyer questions without agent involvement, freeing an estimated 10+ hours per week of phone time. Agents have used that time to take on more active listings without adding headcount.