Globant has deployed agentic AI for Aldar Properties, Abu Dhabi's largest real estate developer, moving the company from AI trials to enterprise-scale deployment. The system, built on Salesforce Agentforce and powered by Data 360, puts AI agents to work on two of the most persistent friction points in the homeowner journey: construction transparency and post-sale service requests.
The rollout sits inside Hello Aldar, the developer's always-on digital concierge and self-service platform. Homeowners can now get plain-language construction updates, submit maintenance requests, and track progress at any hour without waiting for a call back. The agents sort issues automatically, direct them to the right technician, rank urgency, and schedule appointments through existing Salesforce backend workflows.
Two agents targeting specific operational pain points
The Construction Progress Agent converts technical construction data into straightforward updates on milestones, project status, and expected handover dates. The Post-Sale Service Dispatcher handles maintenance and Defect Liability Period requests. When DLP coverage has expired, it automatically routes customers to Inspire Home packages. Both agents work autonomously and anticipate follow-on service needs before a homeowner raises them.
Aldar Properties generates $9.2 billion in annual revenue and carries one of the most ambitious development portfolios in the Gulf. The company faced a problem common across the region: years of customer interactions, service histories, and property records sat siloed and could not drive real-time decisions. Buyers lacked visibility into construction progress, and service teams were overwhelmed with low-value queries. Maintenance requests arrived as unstructured text requiring manual interpretation.
Activating dormant data for always-on service
Globant's solution rewired that model by building a unified customer layer through Salesforce Data 360. The agents query that layer autonomously, turning dormant intelligence into an always-on service layer. Federico Pienovi, CEO of Mena and APAC at Globant, said the region is "architecting the next agentic era with real estate at its centre," and called the Aldar deployment "a reflection of that ambition, converting years of dormant customer data into an always-on service layer that works without being asked."
Harry Nakichband, Chief Digital Officer at Aldar Properties, said homeowners "expect the same intelligence from their property that they experience in other parts of their digital lives," and that the partnership with Globant has enabled Aldar to "deliver real answers in real time at any hour, a standard Aldar is committed to setting across the region."
The AI for Real Estate & Construction deployment reflects a broader regional shift. Private research cited in the announcement shows the Gulf Cooperation Council PropTech sector growing at a 15.7% compound annual rate, projected to reach $5.87 billion by 2032. The wider Mena real estate market is expected to expand 89% from 2026 to 2034. Saudi Arabia's Real Estate Authority recorded SR1.2 trillion ($320 billion) in property transactions during a recent 24-month period.
Salesforce expertise underpins the architecture
Globant brings more than 21 years as a Salesforce partner and over 1,200 projects delivered. The company counts more than 500 Agentforce Certified Specialists and over 200 Salesforce Data 360 specialists. Salesforce has recognized Globant as an Implementation Level Expert for Data 360, MuleSoft, and Agentforce - the highest distinction a Salesforce Solution partner can earn. The announcement follows Globant being named Salesforce's New Logo of the Year for the second consecutive year at the Salesforce Partner Summit in Dubai.
Why this matters for real estate and construction professionals
The Aldar deployment signals a tangible shift in how large developers in the Gulf are using AI. This is not a pilot or a limited trial - it is a production system handling real customer interactions around the clock. For construction and real estate professionals, the takeaway is practical: AI agents are now being deployed to automate the two areas that consistently drain service teams: repetitive status inquiries and unstructured maintenance intake. The AI for Customer Support model shown here reduces manual triage, cuts response times, and converts siloed data into a service layer that works without being prompted. Developers watching this space should note the technical foundation - a unified data layer is what makes autonomous agent action possible, not the agent interface alone.
Your membership also unlocks:
