Real Estate AI Recommendations

Find Homes That Fit Your Life

Helping buyers discover their dream homes faster with AI-powered property recommendations.

PROJECT OVERVIEW

In today's competitive UK property market, where the house-buying process takes “anywhere between three to six months” (First-time buyer statistics UK, 2025) and property portals see 141 million monthly visits from house-hunters, a leading British property portal with over 500,000 active listings wanted to transform buyer discovery.

The platform struggled with overwhelming search results and estate agents spending excessive time on initial filtering rather than closing deals.

We developed an AI-powered recommendation engine using machine learning and buyer behavior analysis, delivering personalised property suggestions and intelligent matching to help UK buyers find homes faster while enabling estate agents to focus on qualified leads.

TECHNOLOGY

Python, Scikit-learn, Geospatial Analytics, Property Data APIs, Behavioral Tracking, Neo4j Graph Database, Redis Caching, RESTful APIs, Machine Learning, Predictive Modeling, Location Intelligence

Client Goals and Objectives

Show personalized property suggestions on the homepage to help buyers find relevant properties faster.

Display map-based property suggestions with area information for better location decisions.

Add lifestyle filters to better match buyers with properties they want.

Show "properties like this" suggestions on listing pages to keep buyers engaged longer.

Give agents dashboards with good buyer leads to reduce time spent on initial searches.

Send automatic property alerts based on buyer preferences to give agents better leads.

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Data Processing
Pipeline

Database
Architecture

AI Agents
Network

Context
Management

Value and Impact Delivered

Faster Property Search

Cut property search time by 60% with smart suggestions.

Better Leads

Provided agents with much better leads by matching buyers with right properties.

Agent Productivity

Boosted agent productivity by 40% with automatic lead filtering.

User Engagement

Increased user engagement with longer visits and more return users.

Market Insights

Provided useful market data and pricing trends to help make better decisions.

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