Jones Lang LaSalle revolutionizes real estate client insights and efficiency
Jones Lang LaSalle (JLL), a global real estate services leader, faced challenges from disparate and inconsistent commercial real estate (CRE) data, hindering client insights and operational efficiency. To address this, JLL partnered with Databricks and Microsoft to implement Azure AI Services, including Azure Databricks and a conversational AI analytics layer in its JLL Azara platform. This AI-driven solution aggregates data across portfolios, democratizes insights, and empowers clients to ask complex questions using natural language. What previously took months of engineering can now be done in minutes or seconds, accelerating business intelligence for facility management, workplace trends, and sustainability initiatives. The solution is integrated with JLL Falcon, their proprietary AI platform, leveraging Microsoft's cloud capabilities for security and scale. Since implementation, JLL's clients can measure workplace performance, discover cost savings, and address sustainability goals more efficiently. The platform provides actionable, real-time data, enhancing decision-making at all business levels and across industries. JLL’s collaboration with Microsoft and Databricks exemplifies the use of cloud-based AI analytics to transform real estate services, reduce operational costs, and support rapid, personalized client insights.
- Organization
- Jones Lang LaSalle
- Industry
- Real Estate
- Location
- Global
Reported outcomes
100%
quantified impactOther quantified impact
Strategic outcomes
Primary read
Use case focus
Showing 3 of 4
- 1Conversational AI Analytics for Commercial Real Estate
- 2Automated Data Aggregation and Insights Discovery
- 3Facility Management Optimization with AI
- Disparate and inconsistent data across commercial real estate portfolios.
- Manual data generation leading to lack of standardized, actionable insights.
- Clients unable to quickly access or interpret data for fast decision-making.
- Operational inefficiencies and high cost of data engineering.
- Implemented Azure AI Services and Azure Databricks to aggregate and analyze data securely at scale.
- Built AI-driven JLL Azara platform offering conversational analytics for clients.
- Leveraged JLL Falcon, an AI platform, to create comprehensive real estate data models and actionable insights.
- Enabled natural language queries, democratizing access to intelligence for all business users.
- Partnered with Databricks and Microsoft for scalable, compliant cloud implementation.
- Reduced time-to-insight for business users from months to minutes or seconds.
- 100% of relevant data now accessible to clients—up from only 30%.
- Helped clients cut costs by millions of dollars through data-driven portfolio optimization.
- Enabled clients to proactively track and meet sustainability goals.
- Hundreds of complex business questions now answered effortlessly each month.
Architecture
JLL's solution leverages Azure Databricks and AI Services for secure data aggregation from multiple sources. The JLL Azara platform, integrated into JLL Falcon, analyzes and models real estate data, enabling conversational AI analytics. Clients use natural language to query the platform, receiving business intelligence powered by the cloud-based Microsoft stack. Databricks provides scalable and compliant data engineering for the end-to-end implementation.
Implementation partners1
Sources & evidence1
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