Photo: Diego M. Radzinschi/ALM

Ogletree, Deakins, Nash, Smoak & Stewart last April became the first law firm to publicly announce a licensing deal with legal AI firm LegalMation, which generates automated responses to complaints in just a couple minutes.

Now, the Atlanta-founded AmLaw 100 firm will be the lone Big Law labor and employment firm to use the tool, announcing Wednesday it signed an exclusive partnership arrangement to use the LegalMation platform and to build new products from it.

Until now, Ogletree had used the product on employment cases in California, but it will expand that use to Texas, New Jersey and Florida as well as other jurisdictions as they become available on the LegalMation platform, the firm announced. In addition to drawing up answers to complaints, the product also drafts responses to discovery requests.

Through the partnership, Ogletree lawyers will train LegalMation's artificial intelligence system and also help in the development of new auto-generated reports through the system. Those reports could include case analytics, case summaries and other high-volume prelitigation tasks, the firm said.

Patrick DiDomenico, the firm's chief knowledge officer, said the license with LegalMation is intended to help the firm's lawyers spend less time on routine legal tasks such as drawing up answers to complaints. Down the line, he said the tool's ability to capture data on complaints will help its lawyers make more insightful decisions while litigating cases.

Patrick DiDomenico, chief knowledge officer of Ogletree Deakins.

“Having access to LegalMation [exclusively] is an obvious benefit,” DiDomenico said. “More importantly, I think it demonstrates the commitment we have to each other. We are both very serious about this partnership. And that is an indicator of how hard we are both going to work to make this mutually beneficial and beneficial to our clients.”

LegalMation, launched in March last year, was co-founded in California by Thomas Suh and Big Law ex-pat James Lee, who also co-founded the litigation boutique LTL Attorneys. The company last year announced a licensing agreement with retail giant Walmart Inc. Suh and Lee have since stepped away from management roles at their firm, which launched in 2003 as a spinoff from Quinn Emanuel Urquhart & Sullivan, to focus on LegalMation's expansion.

Lee said the company's product currently works for four types of lawsuits: employment, personal injury, insurance defense and financial services. The long-term goal is to roll out the tool for jurisdictions across the country.

James Lee

As they work to add jurisdictions, Lee said the company's AI tools will also enable a type of data analysis on complaints that has so far largely eluded the practice of law. The technology can classify up to 2,000 data points on a given complaint, Lee said. That will allow firms, for instance, to compare lawsuits filed by plaintiff's firm, lawyer or jurisdiction.

In the case of wrongful termination claims, Lee said the tool can compare lawsuits based on how long an employee had worked at a company, which can be used as a sign of how serious the case is.

“The biggest challenge in the marketplace today is all the firms and companies have immense data,” Lee said. “The part they don't have is the ability to compare Case A to Case B efficiently and in a way that will give them great insights.”

Comparing cases using LegalMation, Lee said, is “like comparing one Fuji apple's condition to another Fuji apple and then finding relationships.”

DiDomenico, at Ogletree, said the data analysis portion of LegalMation is an exciting development, since it has been difficult to compare cases with one another. Ogletree's data will not be shared with other firms, he said.

“This is one of the first and, I think, most promising tools that can really capture a lot of data that is highly relevant to litigation,” DiDomenico said. “The possibilities are endless in terms of what you can do with that data and how you can analyze it if you have thousands of documents run through this system and millions of data points.”

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