Affinda uses AI to extract important fields from leases:

  • Street number
  • Street name
  • Unit number/Suite
  • City
  • State
  • Post code
  • Country
  • Rent amount
  • Rent frequency
  • First payment 
  • Last payment

Business context and challenge

Extracting information from lengthy leases requires costly manual labor.

Commercial leases are composed of many pages of legal language and complex terms and conditions. This sheer density of information makes these documents difficult to navigate, and often causes crucial information to be overlooked.

Furthermore, lease standards often change, making it difficult for agents to update their records according to new standards, and to track accounting compliance consistently across multiple billing periods.

As a result, contract analytics is a highly involved process requiring entire teams of agents. This traditional solution involves hiring multiple team members to summarize key data — an expensive approach that introduces human error throughout every stage of the process.

Abstracting key information can take agents hours or even days — and the resulting database entries then require a second layer of expert review.

In short, manual data entry leads to wide range of problems:

  1. The necessary man-hours are often prohibitively expensive.
  2. Bottlenecks can appear throughout every stage of the pipeline.
  3. Human-extracted data is highly error-prone and inconsistent.

As a result, the manual data extraction process is frequently so cumbersome and inaccurate that it provides very limited ROI.

Affinda's solution

Extract and summarize all important fields into neatly ordered lists:

  • Address
  • Square footage
  • Base rent
  • Lease commencement date
  • Total area to be leased
  • Term of the lease
  • Expiration date
  • Subletting options
  • Percentage rent
  • Rent escalations
  • Provisions of holdover
  • Landlords’ name(s)
  • Operating expenses
  • Renewal terms

This automatic process of lease abstraction is not only beneficial to real estate agents, but also to lenders or property investors, who can obtain much more data in return for much a much lower time and resource investment

Affinda’s contract AI converts previously unstructured data into data that is structured and ready for analysis. Affinda makes it easy to select extracted fields based on your needs — such as investment, payment monitoring, accounting and reporting, and many others:

  • Ability to analyse portfolio performance and increase ROI
  • Property management optimization, by ensuring payment dates, termination conditions, securite and maintenance terms, and other contractual obligations are followed
  • Accurate accounting and compliance with Financial Accounting Standards Boards (FASB) through extraction of financial data
  • …and much more

Plus, confidence in AI-driven results removes the need for manual review. This saves your business time, while also increasing your level of trust in the extracted information. Affinda’s legal AI document analysis simplifies the information in every contract, making it easily digestible to those without a legal background.

This makes it easy to immediately start capturing ROI from day one, as the vast proportion of fields can be automatically extracted with better-than-human-level  accuracy. 

In the limited number of cases where model accuracy is lower, our solution enhances your team’s performance by enabling a human validation step: when a field requires checking, an agent can review the model output, and amend it as needed. 

This process is not only faster than manually extracting the information — it also provides the added benefit of actually improving the model’s performance through continuous accuracy upgrades.

ROI will continue to increase through ongoing usage as the model gets even smarter at recognizing the lease line items that are most relevant to your organization. 

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