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Case Study: AI in Real Estate

National CRE leader cuts lease data extraction time by 80% with Docugami

 
Document Dysfunction 2-1

A major national real estate company was struggling with the complexities of managing a large portfolio of leases. The team needed an efficient way to extract, analyze, and manage all the vital information contained in thousands of lengthy and complex lease agreements. Using Docugami’s unique Document Engineering, the team cut the time needed to extract data from leases by 80%. 

Drowning in Documents

Commercial real estate is by its very nature a document-intensive industry. Every aspect of leasing a commercial property has to be memorialized in a lease agreement. Every property and every tenant are unique, so lease agreements can be 20, 50, 100 pages or more. The real estate company struggled with the arduous task of extracting, analyzing, and managing key information its extensive portfolio of leases. This information was critical to anticipating renewal dates, renovation schedules, and potential changes in lease terms and pricing. Manual data entry and processing were error-prone and time-consuming. Moreover, identifying lease provisions requiring updates or adjustments required meticulous scrutiny of each document, leading to inefficiencies and missed opportunities for optimization. The company experimented with a number of software solutions, but none gave them the power, flexibility, and accuracy they needed.

Docugami Provides Greater Accuracy and Flexibility

The breakthrough came when the real estate company discovered Docugami. Compared to other software products the company had tried, Docugami required much less setup time and no lengthy IT programming process. Frontline analysts and sales teams could use Docugami immediately and generate critical data from Day One. The team found the initial accuracy surprisingly good, and improved still further as the team optimized the training with their expertise in complex variances.  

Docugami provided greater accuracy and flexibility in unlocking the information in complex lease agreements. Docugami’s unique Document Engineering approach automatically creates a full XML Knowledge Graph representing all the information in every document, and how each piece of information relates to the others, which can then be used in a wide range of powerful ways. From the start, Docugami automated tedious tasks such as identifying renewal dates, identifying pricing, and flagging provisions for review and update. And because Docugami created a full Knowledge Graph of each document, when the team needed to run additional queries across a large group of leases, it could be done almost instantly. 

Greater Efficiency and Insights

Integrating Docugami into its existing workflows was a seamless process. Docugami automatically extracted the key data from large groups of lease documents, and assembled the data into reports that made it easy to identify potential risks and opportunities. The well-organized output, with citations for every extracted piece of data or content, made it easy for frontline leasing agents to check the output and add or correct data points where needed. Docugami also made it easy to funnel key data into the company’s automated workflows where appropriate, which further streamlined operations. Overall, the company estimates that Docugami reduced the time and energy spent on perusing lease documents and extracting information by more than 80 percent. 

Conclusion

By harnessing the capabilities of Docugami’s unique Document Engineering SaaS, this major national real estate firm reduced the time spent by frontline staff managing lease data by approximately 80 percent. The firm saw improved productivity and job satisfaction, greater accuracy than manual data extraction, and improved anticipation of lease renewals, scheduled maintenance, and pricing changes.

Schedule a Demo

Ready to accelerate your real estate operations with Docugami? Our team is eager to show you how our Document Engineering software can be tailored to your unique challenges and goals.