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Real Estate#03 Chat Interaction
Property Recommendation Agent
"Match every buyer to the 3 properties they'll actually love"
92%
Match Accuracy
-48%
Buyer Decision Time
+35%
Inventory Movement
The Problem
Builders showcase 40+ projects but buyers don't have time to evaluate all. The result: confused buyers, longer cycles, and inventory that doesn't move.
Workflow
How the system runs
- 01Buyer preferences captured
- 02Inventory database matched on 12 attributes
- 03Top 3 recommendations generated
- 04Brochures + price list auto-sent
- 05Buyer signals tracked (open, click)
- 06Site visit booking suggested
Customer Interaction
Chat Interaction
NeovraAI Assistant
Active · responding in < 1s
Looking for 3 BHK, 1.5–2 cr, ready possession near IT parks
10:20
Got it. Based on your inputs I'd recommend: Marigold Heights (Hinjewadi), Skyline Residency (Wakad), Lodha Belmondo (Pune). Want detailed brochures?
10:21
Yes, send brochures + price list
10:22
Sent on WhatsApp ✅. Want to schedule site visits this weekend?
10:23
Top 3 matches for you
Atrium ParkIT corridor
Kharadi3 BHK
1.36Cr
Nova NestReady possession
Tathawade2 BHK
72L
Crescent BayLuxury fit
Baner4 BHK
2.1Cr
Type a message…
Dashboard & Reporting
Property Match Intelligence
Property Match Intelligence
Buyer matches accepted
Live
Buyer Profiles Built
3,842
+24%
Recommendation Accuracy
92%
+11%
Brochures Opened
71%
+28%
Shortlist Rate
44%
+16%
Decision Time
−48%
faster
Inventory Moved
₹8.1 Cr
+35%
Buyer matches accepted
Recommendation fit
92%
accepted match score
Ready-possession demand
46%
top segment
Brochure-to-visit
39%
+14%
Unsold stock surfaced
128 units
matched
Operational Improvement
Before vs After
Before
- Buyers receive generic brochures
- Reps push whichever inventory they remember
- Premium units buried in spreadsheets
- No learning from buyer behaviour
After
- Every buyer gets a ranked shortlist
- Inventory matched on budget, area, possession and lifestyle
- Open/click signals improve next recommendation
- Management sees demand by micro-market
Business Impact
Measured outcomes
92%
Recommendation Accuracy
48%
Decision Time Reduction
+35%
Inventory Velocity
3x
Brochure Engagement
Technology Stack
Enterprise architecture
3-week build · production-grade infrastructure
Automation Layer
- Make.com / n8n
Communication Layer
- WhatsApp Business API
CRM Layer
- HubSpot CRM
- Airtable
Calendar & Booking
- Calendly
Voice Layer
- Twilio
Suitable Industries
Residential Real Estate Luxury Real Estate Brokerage Firms Automotive Dealerships Education Programs Travel Packages
Implementation Brief
Property Recommendation Agent rollout plan
Architecture, integration layers, operating rhythm and KPI governance for a 3-week production rollout.
System Walkthrough
6-step workflow · 6 KPI dashboard · chat interaction model
Project Note
"Buyers don't want 40 options. They want 3 great ones. This agent does that thinking for them in under a minute."
Project Concept & Design
Anurag Dube
Developed Under
NeovraAI