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Real EstateAI

Bayut Premium AI

Real estate portal, Dubai

Key outcome4h → 90s response
90s
Avg. response time
94%
Enquiries handled automatically
+38%
Qualified leads per month
The challenge

What needed
solving

A high-volume Dubai property portal was receiving 800+ enquiries per day across WhatsApp, email, and web forms. Agents were spending 3–4 hours daily triaging messages, and serious buyers were waiting hours for a response — by which time many had moved to a competitor. The manual process created inconsistent tone, missed follow-ups, and no visibility into lead quality.

The solution

What we built

We built an AI lead qualification pipeline that intercepts every inbound enquiry in real time. A GPT-4o model reads the message, scores intent (hot/warm/cold), extracts buyer requirements, and generates a personalised WhatsApp response within 90 seconds — 24 hours a day, 7 days a week. Hot leads are escalated to an agent with a full context brief. The entire flow runs on n8n with a HubSpot CRM integration, and a real-time dashboard gives the sales manager full visibility into volume, quality, and agent response times.

Tech stack
GPT-4oWhatsApp Business APIn8nHubSpot CRMNode.jsPostgreSQL
Category
Real EstateAI
Results

The numbers

Concrete, measurable outcomes delivered in production.

90s
Avg. response time
94%
Enquiries handled automatically
+38%
Qualified leads per month
How we work

From brief to production

01

Discovery & scoping

We map the problem, understand the existing stack, and write a fixed-price proposal. No surprises.

1–3 DAYS
02

Build & weekly demos

You see working software every week. Feedback is incorporated immediately — not at the end.

2–6 WEEKS
03

Testing & QA

Every integration is stress-tested before go-live. Edge cases handled, fallbacks in place.

3–5 DAYS
04

Go live & handover

Full documentation, team training, monitoring setup, and 30-day post-launch support.

1 WEEK

Build something similar?

Book a free 30-minute call. We'll assess your situation and tell you exactly what we'd build — and what it would cost.

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