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Lex Machina Launches State Law Modules, Extending Its Groundbreaking Legal Analytics to State Courts in California and Texas

Los Angeles County Superior Court, Harris County Court and Harris County District Court are the first new offerings; extensive new features for state courts include entity and document searching

Lex Machina provides award winning Legal Analytics, a new category of legal technology that profoundly changes how companies and law firms compete. Legal Analytics allows law firms and companies to predict the behaviors and outcomes that different legal strategies will produce, enabling them to win cases and close business. Lex Machina is used by companies such as Microsoft, Google, and eBay, and law firms including Wilson Sonsini, Fish & Richardson, and Fenwick & West. (PRNewsFoto/Lex Machina)

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Lex Machina

Feb 04, 2020, 08:00 ET

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MENLO PARK, Calif., Feb. 4, 2020 /PRNewswire/ -- Coinciding with the 10th anniversary of its award-winning Legal Analytics® platform, Lex Machina, a LexisNexis company, today announced an exciting new expansion into state court analytics. Consisting of more than 870,000 cases in Los Angeles County and Harris County (Houston metro area), the new modules give practitioners critical insights about judges, courts, law firms, individual attorneys and parties in state courts. By leveraging its Attorney Data Engine and other natural language processing technology, Lex Machina is the only legal analytics provider able to utilize state court documents to provide comprehensive coverage about the behavior of judges, law firms, attorneys and parties in state courts.

Lex Machina is solving an immense technical challenge by taking complex, unstructured data and utilizing its software to allow practitioners to make data-driven decisions, develop winning case strategies and win new business in brand new state court venues. Because there is no unified system for state courts analogous to PACER in federal courts, Lex Machina will add its new State Court modules on a court-by-court basis, with an emphasis on strict data quality and integrity to ensure that legal professionals have access to the most complete, comprehensive and accurate analytics available.

Lex Machina worked closely with the court systems to understand their docketing practices and create analytics that reflect the unique aspects of individual courts. For example, the three new state courts – Los Angeles County Superior Court (615,000+ cases), Harris County District Court (175,000+ cases) and Harris County Court (80,000+ cases) – each have their own data collection infrastructure and nuances. The new modules, and thus the substantial case numbers, cover four years of court activity beginning with cases filed January 1, 2016 or later.

The Los Angeles and Houston courts were selected for the initial release because they represent important data sets to understand the overall process of developing state court analytics. Los Angeles County Superior Court is the largest state court in the nation by volume. Harris County encompasses a large metropolitan area and is part of Texas' two-court civil system, with the Harris County District Court of general jurisdiction and Harris County Court of limited jurisdiction. Lex Machina developed relationships with these three courts and was able to gather feedback from users practicing in Los Angeles and Houston. Lex Machina plans to expand its state court coverage to a dozen U.S. state courts in 2020, including many major metropolitan areas.

"It's an exciting technical challenge to responsibly expand our coverage to include complex analytics for state courts, where even basic information such as who was involved in the case is buried in millions of pages of court documents. Electronic filing systems across states and districts are unique to individual courts, so structuring and normalizing the data to make it usable and reliable is notoriously difficult," said Karl Harris, Lex Machina's CEO. "In spite of these obstacles, we've now laid the foundation to bring Legal Analytics to state courts all over the country, and customers familiar with our interface for federal courts will see that our state court modules work similarly. This is an incredible accomplishment."

Lex Machina gathers raw information from state court cases, including downloading millions of state court documents to present the most comprehensive and accurate data possible. The company cleans, tags, codes, enhances and presents the resulting data in a way that makes it easy for users to quickly access insights and grasp trends that are relevant to the legal matter they're working on. Whether simply searching for a case or looking for more in-depth analytics, practitioners can investigate a party's litigation track record, assess a law firm's experience in similar cases, observe patterns in judicial decisions, examine the range of damages awarded at trial or search docket entry text.

Both new and existing Legal Analytics users will appreciate the easy-to-use interface that lets them access a wealth of new state court features including:

  • Searching by judge, law firm, attorney name or party
  • Timing analytics, trial resolutions, trial damages and trial rulings
  • Keyword searching within docket entry text and downloaded documents
  • Viewing analytics across all state courts or in one particular court
  • Court-specific filters, such as case types and case tags

The introduction of the new State Law modules complements Lex Machina's first foray into state law analytics, the highly specialized Delaware Court of Chancery, which launched in January 2018. Over the past 10 years, Lex Machina has released modules for 15 federal practice areas, including antitrust, bankruptcy, consumer protection, contracts, copyright, employment, environmental, ERISA, insurance, patent, product liability, securities, tax, trademark, and trade secrets. It will continue to work on releasing new federal court practice areas as well as new state courts later this year.

State Law Analytics at Legalweek: Expanding the Legal Analytics Footprint
On Tuesday, February 4 from 3:30 to 4:30 p.m. in the Rhinelander Theater (2nd floor), Karl Harris, CEO, Lex Machina will join Eric J. Felsberg, Principal, Jackson Lewis; Catherine A. Bernard, US Litigation Professional Support Lawyer, Mayer Brown; and Angela Ni, Director of Underwriting and Data Science Strategies, Corporate Counsel, Parabellum Capital to discuss how Legal Analytics is transforming the full litigation cycle from new client acquisition all the way through trial. They will explore the key factors leading the expansion of analytics in today's data-driven environment, how lawyers are leveraging analytics to make their practices more competitive and the challenges of bringing comprehensive analytics to state court litigation data.

About Lex Machina
Now celebrating the 10th anniversary of Legal Analytics, the Lex Machina platform fundamentally changes how companies and law firms compete in the business and practice of law. The company provides strategic insights on judges, lawyers, law firms, parties and other critical information across 15 federal practice areas, the Delaware Court of Chancery and select state courts. This allows law firms and companies to predict the behaviors and outcomes that different legal strategies will produce, enabling them to win cases and close business.

Legal Analytics was named "Best Legal Analytics" (The Recorder, 2014, 2015, 2016), "Best New Product of the Year" (American Association of Law Libraries, 2015), a "Legal A.I. Leader" (The National Law Journal, 2018), "Best Decision Management Solution" (AI Breakthrough Awards, 2019), and "Disruptor of the Year" (Changing Lawyer Awards, 2019). Based in Silicon Valley, Lex Machina is part of LexisNexis, a leading global provider of legal, regulatory and business information and analytics. For more information, please visit www.lexmachina.com.

SOURCE Lex Machina

Related Links

http://www.lexmachina.com

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Lex Machina, a LexisNexis company, recently released expanded and enhanced Legal Analytics for the remainder of its federal district court dataset,...

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