A brokerage that stopped losing leads to slow response times.
Real Estate
Case study narrative
The business problem
A growing real estate brokerage was converting inbound leads inconsistently — not because the leads were bad, but because qualifying them depended on whichever agent had a free moment. By the time someone followed up, a meaningful share of leads had already gone with whoever responded first.
The solution
A conversational AI agent that qualifies every inbound lead within seconds — asking the right questions, flagging serious buyers, and routing them to the right agent automatically, day or night.
Technologies used
A conversational AI agent connected directly to the brokerage's existing CRM — deliberately ordinary, well-understood infrastructure. The value here is the judgment built into the conversation, not an exotic stack.
Implementation process
Two weeks to map the brokerage's actual lead sources and qualification criteria, one week to build and test the conversational flows against real (anonymized) past inquiries, a phased rollout starting with a single lead source before expanding to all of them, and two weeks of live tuning once agents started seeing real conversations come through.
Business impact
Agents stopped competing for whoever happened to be free when a lead came in — every lead now gets the same fast, consistent first response, and the team spends their time on qualified conversations instead of triage.
Measurable results
40%
faster first response
24/7
lead coverage, no gaps overnight
0
leads left unqualified by morning
What we’d do differently
The agent's early scripts asked too many questions up front, which quietly hurt completion rates. The fix: qualification has to feel like a conversation, not a form — even when a machine is running it.