Dubai, UAE, 24th September 2025, ZEX PR WIRE, An award-winning, UAE-based property-intelligence start-up that gained international recognition for its real-time analytics has marked a significant development in the region’s PropTech sector. Research 247-UAE, which developed machine-learning models to process property data across all seven emirates, recently completed its operational phase. The company achieved notable market penetration, processing a substantial portion of Dubai’s freehold transactions and providing hourly updates on market indicators. The company’s analytical approach earned recognition within the technology sector; it was featured by Gartner and secured positions in regional rankings of fast-growing property-technology companies.

Role of core team

Balaga Raghuram, who served as a machine-learning research consultant and led the global team during the platform’s development, explained the technical approach: “The system processed real-time feeds from multiple sources, including transaction records, listing platforms, economic indicators and external factors that might influence buyer behaviour.”
The platform covered major UAE markets, from Dubai’s established luxury sector to emerging areas in Ras Al Khaimah and Fujairah, supplying analytics on price trends, inventory levels and market sentiment.

Industry recognition

Presenting the models at academic conferences

“Participating in academic conferences proved vital for research development,” noted Balaga Raghuram, who presented analytical approaches at the Oxford University Conference, focusing on AI applications in real-estate valuation and investment decision-making.

Market impact and Insights

Implementation of the platform’s analytics showed measurable effects: some clients reported improved investment outcomes, and real-estate agencies observed increased user engagement when integrating AI-driven insights. The technical infrastructure combined various data streams to create comprehensive market views, processing information from traditional property records alongside alternative data sources.