AI-Powered Property Matchmaking

1. The Challenge

A leading French real estate agency was struggling with the manual process of browsing and filtering through thousands of property listings stored in PDF format. Each file varied in structure, language, and layout — making traditional keyword search unreliable.

Their sales agents needed:

• A faster way to find relevant property listings based on client needs
• A system that could understand unstructured, PDF-based property data
• A smart, intuitive assistant accessible directly from internal tools
• A scalable solution for handling continuous document inflow

2. The Solution

We developed and deployed a custom AI property recommendation assistant powered by natural language understanding and Retrieval-Augmented Generation (RAG) techniques.

Key features of the solution included:

• Parsing and embedding thousands of heterogeneous PDF listings
• Semantic search and ranking of properties based on agent queries
• Integration with a secure internal chat interface (supporting free-text input like “Client wants a 3-bedroom apartment with balcony in Lyon”)
• Built-in summarization of property highlights from full PDFs
• Auto-updating index to continuously reflect new listings

The assistant allowed agents to skip the manual document digging and instantly access the most relevant options — in plain language.

3. The Result

The impact on the client’s internal workflows was immediate:

80% reduction in time spent searching for matching listings

• Enhanced ability to respond to client requests in real-time
• Higher agent satisfaction and improved closing rates
• Reliable discovery of hidden gems from large, messy PDF inventories

The AI assistant is now an essential part of daily operations, helping sales reps deliver faster, more accurate, and more tailored property recommendations.