Will Sakkini change the face of house hunting in the UAE?

If you live – or have ever lived – in the United Arab Emirates, chances are you are familiar with just how tedious and soul crushing house hunting can be. From difficult landlords to misleading advertising, buying or renting a property in Abu Dhabi, Dubai or the rest of the Emirates can often lead to wasting precious days or weeks searching for the right apartment, not to mention potentially losing thousands of dirhams in hidden costs along the way.

Funnily enough, it was during Haitham Al-Khatib and Faisal El-Hoseni’s own home searches last summer that their idea for the startup, Sakkini was born.

“We were both looking for apartments in Abu Dhabi, and we had a broad idea of what we were looking for,” says founder and general manager Al-Khatib. “We took it upon ourselves to drive around town and look for apartments, but that ended quickly, because it was hard find availability, and building management didn’t have the information we needed.

“We then searched on Propertyfinder and Dubizzle, and while we were happy to see so many properties that met our criteria, after contacting the agents we found out that these properties were either unavailable or the price was falsely advertised.

“We eventually realized that the listings advertised were just phishing techniques employed by real-estate agencies, so we decided to dig deeper to find the root of the issues… spending countless hours with real-estate agents, analyzing their day-to-day operations to find the bottlenecks and problems they are facing. We narrowed down the problem and found a solution that satisfies both home-seekers and agents.”

What it does

Set to launch this June, Sakkini is a data-driven property platform that aims to empower home-seekers with the tools and information they need to make smarter decisions about property that’s either for rent or sale.

“It provides home-seekers with insights into what amenities and services are available in a neighborhood,” Al-Khatib continues. “We also use historic data, along with machine-learning algorithms to give home-seekers price indicators that aim to build more transparency and confidence in the market.