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Real estate / PropTech

AI Viewing Booking Agent

Viewing coordination was consuming the equivalent of half a working day per adviser in peak periods. entirely through manual, interruptive tasks that a structured AI agent could handle.

Timeline
Four week build with a two week parallel run period (agent and adviser coordinating simultaneously) before the agent was given primary responsibility for the booking function.
Scope
Process mapping of existing viewing coordination workflow, AI agent design and script development, escalation protocol definition, CRM integration, and performance monitoring setup.
Model
The parallel run period was deliberately included to surface edge cases before the agent operated independently. Every escalation during that period was reviewed and used to improve the decision boundary, we shipped the agent as a collaborator first, not as a replacement, and the handover happened when the team felt confident rather than on a fixed calendar date.

The outcome

AI calling agent deployed for outbound viewing bookings. coordinating availability, confirming slots, and logging outcomes. freeing adviser time.

BOOKING TRIGGERSClient preferencesViewing requestAgent contact listSchedule constraintsCRM case recordAI CALLING AGENTOutbound call executionBooking, voicemail, callbacksequencesRescheduling flowsHandles cancellations and agentno-showsEscalation protocolNon-standard conditions to adviserhandoffOUTPUTBookingConfirmedConfirmed viewing slotCall transcript + logCRM auto-updatedAdviser time -85%

Findings

What we built it around.

01

AI calling agent with defined outbound scripts covering initial booking, voicemail handling, callback acknowledgement, and rescheduling flows

02

Client preference intake layer

structured criteria capture (preferred days, travel constraints, co viewer requirements) feeding the agent's scheduling logic

03

Escalation protocol

defined conditions under which the agent pauses and routes to an adviser, with context handoff so the adviser doesn't start from scratch

04

Call recording and transcription pipeline

full audit trail of all agent interactions with agents and property managers, stored against the relevant CRM case

05

CRM integration

automatic pipeline stage update on confirmed booking, with viewing details and agent contact logged without manual entry

Results

What changed.

01

Viewing coordination time for advisers reduced from 4, 5 hours per day at peak to under 45 minutes of exception handling, a reduction of approximately 85% in active adviser involvement in the booking process

02

Callback and voicemail handling fully automated: the agent manages multi attempt outreach sequences without adviser intervention, resolving the primary source of coordination delay

03

Viewing confirmation rate improved: structured follow up sequences reduced the incidence of unconfirmed viewings showing up in the diary, a problem that had previously resulted in wasted travel and client dissatisfaction

04

Institutional knowledge captured: agent contact preferences, response patterns, and rescheduling history are now logged systematically, eliminating the informal knowledge loss that occurred when staff changed roles

05

CRM pipeline accuracy improved as a byproduct: viewing stage updates are now recorded in real time rather than entered retrospectively, making pipeline reporting more reliable

Takeaway

AI calling agent deployed for outbound viewing bookings. coordinating availability, confirming slots, and logging outcomes. freeing adviser time.

Real estate / PropTech

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