Property enquiry assistant
Collect budget, location, timing, property type, financing status, and contact preferences.
Start a ProjectProperty teams can use AI agents to qualify enquiries, prepare viewing requests, collect seller or landlord details, and help agents respond with better context.
Buyers, tenants, sellers, and landlords often ask similar questions, but each enquiry needs enough context before an agent can act.
Start by improving enquiry intake and handover quality before connecting property feeds, CRM updates, or valuation workflows.
Collect budget, location, timing, property type, financing status, and contact preferences.
Prepare viewing requests with preferred times, property reference, and visitor details.
Collect property details, reason for selling, area, condition, and preferred next step.
We design agents around the small handoffs that happen every day: enquiries, reminders, document requests, summaries, and approvals.
The agent can help separate casual browsing from serious purchase intent.
Tenant enquiries can include move-in date, budget, household needs, and document readiness.
Agents can receive a short summary before calling back.
The first version should be narrow, useful, and easy for your team to supervise. Once the workflow is trusted, it can be connected to more systems and more customer touchpoints.
AI agents should not guess, overpromise, expose private data, or replace professional judgement. We build the boundaries before we build the conversation.
The agent should not promise viewings or availability without trusted listing data.
Tenant and buyer workflows should avoid discriminatory questions and routing.
Valuation and negotiation advice should remain with qualified property professionals.
Yes. It can collect useful context and prepare a handover so agents spend more time with suitable prospects.
It can request or coordinate viewings. Confirmation should depend on agent availability and property status.
Yes, once the lead fields, ownership rules, and review points are clear.