A sea of dashboards hid 70% of data. Now, users query portfolios via a conversational tool, cutting insight time from months to seconds.
A global commercial real estate services leader with over 200 years of experience, supporting occupiers and investors through portfolio management and leasing.
The industry faces a "wide data" problem with manually generated and dirty datasets, leaving 70% of information historically inaccessible to clients....
“In the AI revolution, Microsoft and Databricks have been the fastest to figure out how to unlock business value out of technology. Azure has been a leader on the cloud front and provides the full stack, from the infrastructure to the platform to the AI, streamlining implementation and delivery.”
JLL's Real estate portfolio analytics is part of this use case:
Commercial real estate services and investment management firm.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Collaborated with JLL to design a secure solution for data aggregation and AI-driven insights.
Related implementations across industries and use cases
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Rigid filters forced buyers to act like admins. Now, they describe a "cottage feel," and AI scans millions of listings to find a match.
Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
A sea of dashboards hid 70% of data. Now, users query portfolios via a conversational tool, cutting insight time from months to seconds.
A global commercial real estate services leader with over 200 years of experience, supporting occupiers and investors through portfolio management and leasing.
The industry faces a "wide data" problem with manually generated and dirty datasets, leaving 70% of information historically inaccessible to clients....
“In the AI revolution, Microsoft and Databricks have been the fastest to figure out how to unlock business value out of technology. Azure has been a leader on the cloud front and provides the full stack, from the infrastructure to the platform to the AI, streamlining implementation and delivery.”
JLL's Real estate portfolio analytics is part of this use case:
Commercial real estate services and investment management firm.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Collaborated with JLL to design a secure solution for data aggregation and AI-driven insights.
Related implementations across industries and use cases
Staff struggled to spot correlations across thousands of data points. Now, a multi-agent system answers voice queries in under 3 seconds.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Rigid filters forced buyers to act like admins. Now, they describe a "cottage feel," and AI scans millions of listings to find a match.
Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Data silos blocked real-world simulation. Now, teams validate site physics and safety risks on a unified digital twin.
Scattered expertise across 40 engineering topics slowed global teams. Now, an AI agent instantly surfaces secure, curated best practices.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.