Dubai-based startup dataHabibi has officially launched an AI-powered intelligence platform designed to transform how property market data is analyzed. Founded by Ibrahim Qorraj and Haron Merzaie, the platform aggregates complex information—including building prices, rental yields, transaction histories, and future project forecasts—into a unified research interface. By focusing on market evidence rather than property listings, the startup aims to provide buyers, investors, and industry professionals with a clearer, data-driven perspective on the Dubai real estate market.
The platform addresses a common challenge in the local market: while information is abundant, interpreting it to make informed financial decisions remains difficult. Unlike many services that merely integrate chatbots, dataHabibi embeds artificial intelligence directly into the research workflow. The system automatically organizes records, compares building performance, tracks market momentum, and updates forecasts daily, ensuring users have access to current signals rather than outdated reports.
Qorraj emphasized the practical utility of the tool, stating, “AI should earn its place by making a hard decision easier.” He noted that because the Dubai property market moves at a rapid pace, it is nearly impossible for individual buyers or agents to manually review every relevant record. The platform is designed to handle this heavy lifting, presenting complex data in plain language to facilitate faster, more confident decision-making.
The current suite of tools available on dataHabibi includes comprehensive project research, developer intelligence, off-plan pipeline data, and a dedicated Dubai property price index. Looking ahead, the company plans to expand its capabilities to include automated valuation ranges, professional-grade PDF reports, and personalized alerts regarding changes in yield or deal activity. These features are intended to help agents and investors save time while providing a more robust foundation for their clients.
Haron Merzaie highlighted the importance of transparency in high-stakes financial commitments. “Property decisions often involve a family’s largest asset or an investor’s largest commitment,” Merzaie said. “People deserve more than an asking price and a sales pitch. They should be able to see the market evidence, understand the trade-offs and decide with confidence.”
The launch of dataHabibi aligns with the UAE’s broader National Strategy for Artificial Intelligence 2031, which emphasizes the role of AI in driving economic growth and enhancing efficiency across key sectors. By leveraging the city’s digital public services and open market activity, the startup aims to provide a level of analytical access that was previously reserved for specialized research teams.
To maintain objectivity, the platform operates without property listings or advertisements. The business model offers core research tools for free, while a Pro tier provides deeper access to historical transaction data and advanced investment analysis. While the company is currently focused on the Dubai market, the founders believe the underlying technology is scalable and could eventually be applied to other cities where property data is fragmented or difficult to navigate.
Ultimately, the success of the platform will be measured by its ability to help users save time, identify stronger opportunities, and avoid poor deals. By prioritizing evidence-based insights over speculative predictions, dataHabibi seeks to establish a new standard for property intelligence in a market defined by its speed and complexity. The report also notes that agents can pull reports and investors can spend hours comparing buildings, buyers can find asking prices. The report also notes that the harder task is deciding which facts matter and what they say about a property before money changes hands. The report also notes that not an advert, the product has a clear point of view: property research should start with market evidence. The report also notes that that approach matters in a market where two similar homes can carry very different asking prices. The report also notes that a buyer may want to know what comparable units recorded in recent deals. The report also notes that an agent may need a sound client brief within minutes.
Source: Khaleej Times
