Daleel co-founder on why Dubai’s property market needs AI-native intelligence
A core promise of Daleel is that it does not tell users what to buy. Instead, it shows what the data says and leaves the decision to the user
07 February, 2026
TT
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Daleel has officially launched at PropTech Connect Dubai with an ambition that cuts to the core of one of real estate’s most persistent challenges: bias.
Unveiled under the Dubai Land Department’s Real Estate Evolution Space (REES) programme, the AI-native real estate intelligence platform combines verified government transaction data with conversational artificial intelligence to deliver institutional-grade insights across Dubai’s $100bn property market. The launch was accompanied by a $3m pre-seed raise.
Founded by former Dubai broker Ilan Cohen and AI specialist Ely Weichsel, Daleel positions itself as a data-first alternative to opinion-driven property advice. The platform allows agents, brokers, investors and buyers to ask natural-language questions, from yield comparisons to rental performance, and receive answers grounded in official Dubai Land Department (DLD) data, rather than asking prices or sales narratives.
“Daleel is the Arabic word for guide,” Cohen explained. “And this is exactly what we are bringing to the market. We are bringing clarity.”
The idea for Daleel was born out of Cohen’s own experience on the front lines of Dubai’s real estate market. Over five years, he closed hundreds of millions of dirhams worth of transactions — and found himself repeatedly constrained by the inefficiency of existing tools.
“I was wasting a lot of time when I wanted to search for a property, whether to buy or to rent,” he said. “I would go on listing platforms, compare price per square foot, understand rentals, floor plans, views, then cross-check everything against DLD data from other platforms. After that, I still had to run financial and investment analysis before sending anything to a client.”
That process limited scale. “The maximum I could handle was maybe five or ten clients at the same time,” Cohen said.
The breakthrough came when he approached his co-founder with a simple question: could AI sit on top of a unified data layer and answer complex real estate questions instantly?
“I asked, ‘Would it be possible to use data as a central database, and then just ask whatever question I have?’” Cohen recalled. “I don’t want to search for hours. I want the investment report in one go.”
The result is Daleel: a conversational AI directly connected to DLD data through the REES incubation programme, designed to surface facts, scenarios and risks — without recommendations.
Removing bias by design
A core promise of Daleel is that it does not tell users what to buy. Instead, it shows what the data says and leaves the decision to the user.
“When you create an AI, you decide its profile,” Cohen said. “And our AI will never tell you ‘invest there’ or ‘do this’. It will only show you whatever is true in the market from your research, and you take the decision.”
That design choice is deliberate. Cohen described being approached by market participants asking whether paid listings or prioritisation could influence outputs.
“That’s exactly what we never want to do,” he said. “You cannot create a strong real estate market if investments are made on bias.”
In traditional brokerage models, multiple agents often offer conflicting advice, shaped by incentives rather than data. “You call one agent, you get his view. You call another, you get hers. Everyone has a bias or an interest,” Cohen said. “If you convince people that their investment is grounded in data, you remove that feeling afterwards of being pushed into something they didn’t really want.”
The conviction behind Daleel resonated early with investors. Cohen said the platform secured backing before a live product existed.
“One of my largest investors is also a large property investor in Dubai,” he said. “He owns more than Dhs100m in properties that he purchased with me. I pitched him the idea and now we have the product you see today.”
The response was immediate. “He understood the meaning and said, ‘I want it,’” Cohen said. “He trusted that if this could come to market, it could be revolutionary.”
That belief translated into the $3m pre-seed round, backing a platform that positions AI not as a marketing layer, but as a structural upgrade to how property intelligence is consumed.
From Dubai to the wider GCC
Dubai is deliberately Daleel’s starting point. “My experience was Dubai, so it felt like the right place to start,” Cohen said. “We needed government data, and DLD provided it.”
Once the model is proven, expansion follows a phased approach. “First Abu Dhabi, then Ras Al Khaimah,” he said, before turning to Saudi Arabia.
“Saudi is at a big inflection point,” Cohen noted. “They are opening to international investors, and at the beginning it’s always hard because there is no data base. The chance they have is to create the market on a healthy base, and this is what we are ready to bring.”
While Daleel has launched with a freemium model, its commercial focus is firmly B2B. The platform can be white-labelled for brokerages, developers and family offices, embedding proprietary data, pitch frameworks and negotiation strategies within the AI interface.
“They could have their own logo, their own data, their own way to orient sales or negotiation,” Cohen said. “They just share a link, and everything is there.”
Success, he added, will not be measured by a single metric. “We want to see how regular people use it, how brokers use it, how developers use it, and which category is most inclined to adopt it,” he said. “That will show us the right way to scale in the Emirates and across the GCC.”
With seven internal staff, 15 external contributors, and early traction at launch, Daleel enters the market at a moment when AI-native platforms are moving from experimentation to infrastructure. Its bet is that in real estate — where trust, data and capital intersect — clarity may be the most valuable asset of all.
Read: Dubai property sales hit Dhs51.1bn in August, up 7.9 per cent YoY
