every lead answered, every renewal priced

a leasing system that engages every prospect in seconds and prices every renewal with math you can audit

Leasing runs on speed, and most leasing teams lose on speed. A prospect fills out a form on Friday afternoon and hears back Tuesday, after they have already signed somewhere else. A renewal that should have started four months out goes out past the notice deadline. The work that loses these deals needs no judgment, and yet it eats the hours of the people who could be closing.

Built the system that does that work end to end, with a person in control of every message that leaves the building.

the full lifecycle

From first inquiry to signed renewal. It answers every inbound lead within seconds across SMS, email, and voice, pulls out what the prospect wants (unit size, move-in date, budget), qualifies them against the property’s criteria, and books a tour against real agent availability. After a showing it collects the agent’s feedback and sends the matching follow-up. When a unit opens, it scores waitlisted prospects and drafts the outreach for approval.

the renewal engine

On the retention side it begins outreach 120 days before expiry, setting the tone from the tenant’s tenure and payment history. Before any offer goes out, a pricing engine recommends a renewal rent from five weighted factors: market comps, retention risk, payment history, lease-term value, and the cost of leaving the unit vacant. It respects the minimum and maximum bounds the operator configures, flags statistical outliers for a human, and logs the full calculation, so every price can be explained later. When a tenant counters, it tracks each round and suggests responses inside policy, then escalates to a person the moment the gap stops narrowing or the tone turns.

how much it runs on its own

Every outbound message waits for human approval before it sends. Past that, the team chooses how much rope to give it across four modes: full autonomy behind approval gates, AI drafts for a human to approve, AI sends after a review window unless someone vetoes, or AI steps back entirely and a person takes the wheel. The setting moves per property and per situation.

compliance built in

Leasing is regulated, so the system is built to be examined. Every qualification decision rests only on objective criteria the operator defines. Every AI action is logged with its inputs and reasoning. Periodic checks flag statistical disparities across demographic groups, and the audit trail is retained for as long as the operator needs it. It also resolves the same prospect who texts, emails, and calls from three different numbers into one contact, and routes a lead to a sister property when the one they contacted has nothing that fits.

what it frees up

A leasing professional’s edge is the conversation: reading a prospect, building trust, closing. Tour confirmations, voicemail transcription, and follow-up nudges borrow that time and give nothing back. Hand the repetitive cycle to a system that answers instantly, prices defensibly, and keeps a person on every decision, and the team spends its hours where deals are actually won.