Real-Estate Lead Lifecycle System

Knight Frank’s commercial property desk was running three separate outbound jobs by hand: refreshing the owner database to surface live requirements, alerting every contact the moment a new listing went live, and chasing interested leads until they converted or went cold. Each is repetitive, time-sensitive, and exactly the kind of process that degrades when it depends on individual rep memory. We built a sequenced three-agent voice AI pipeline, with each agent owning one stage of the lifecycle. Jacqui runs continuously, qualifying the database on a disciplined eight-week cycle and surfacing any buy, sell, or lease requirement. Gabbi fires on every new listing, promoting it to the full eligible database, capturing interest, and sending the information memorandum – and if a contact isn’t interested in that property, she pivots straight into Jacqui’s requirement check. Becky then takes Gabbi’s interested contacts through a fixed three-week follow-up, classifying every outcome as hot, warm, or cold. Each agent hands off to a human only at the moment real intent appears, and all three respect a shared opt-out list. The result is a database kept permanently warm, every listing promoted instantly, structured hot/warm/cold reporting per listing, and human time spent only on deals actually forming.