Picture yourself as a new litigator, set to try an important case before an unknown judge. What if you could access, in advance of trial, a trove of helpful information about this judge? What if you could find out whether she leans plaintiff or defendant, how she usually rules on summary judgement motions, or how quickly she typically processes cases?
I’m willing to bet that both you, and your clients, would find this information highly valuable. This is exactly the inspiration behind a new company, Gavelytics, a legal technology startup which launched on September 26th out of Santa Monica California. It aims to help litigators learn as much as they can about a judge before they go to court. Gavelytics uses artificial intelligence, machine learning, and natural language processing to analyze large quantities of court dockets and litigation data, and then compact and organize this data for use by litigators.
But, of course, all of this valuable information comes at a price. Gavelytics has not disclosed its specific pricing details, but has said that its pricing is based on a monthly subscription to its services, with rates varying based on the product mix a firm selects. Currently, Gavelytics only covers information from superior courts in Los Angeles and Riverside counties in California, but has bold plans for expansion, hoping to extend its services to the entire state of California by next year, and eventually on to other states.
Although Gavelytics is the newest company to venture into the realm of judicial analytics products, it is not the first. Lex Machina, Ravel Law, and ALM Perspectives are the other existing companies in the U.S. which currently provide this type of analytics. Lex Machina, a product of LexisNexis, was founded in 2006 and specializes in analyzing intellectual property cases, and allows users to access data such as a judge’s likelihood of finding a patent unenforceable, or the average amount of damages the judge awards. Ravel Law’s Court Analytics platform, founded in 2016, boasts a large jurisdictional database covering more than 400 federal and state courts, giving insights into an arguments’ likelihood of success in a given jurisdiction. ALM Judicial Perspectives, also founded in 2016, focuses on providing detailed biographical and historical information about judges, including news stories which judges appear in.
This burgeoning technology has the potential to greatly alter how lawyers prepare for litigation,
allowing them to precisely tailor their briefs according to their judge’s preferences, customize their litigation strategy from judge to judge, intelligently manage client expectations, and generally have a leg up on opposing counsel which does not use these services. Examples of the kinds of insights provided by these judicial analytics platforms include:
Judge Susan Illston in the Northern District of California grants 60% of motions to dismiss, which makes her 14% more likely to grant than other judges in the district
The 2nd Circuit is most likely to turn to the 9th Circuit for persuasive caselaw, and then to the 5th and 7th circuits
Measured by citations, Judge Richard Posner truly is the most influential judge on the 7th One of Posner’s most cited decisions is Bjornson v. Astrue . . . [t[he most important passage of that decision is on page 644
This sample is an example of the kinds of data provided to users by Ravel’s Court Analytics Program. Each of these platforms promises to generate similarly shrewd results, data which is so in-depth that it might often go undiscovered without tools such as these. While some point out that this kind of in-depth legal research is still possible without resorting to judicial analytics platforms, proponents hope that these platforms will make access to this kind of data cheaper and more widely accessible, with the added potential to increase meaningful access to justice for vulnerable clients.
Although it remains to be seen how judges actually feel about these platforms, one can imagine that some judges may not be too thrilled to discover that detailed records of their personal biases and behavioral patterns are being compiled and sold on the open market. Many judges may be worried to see that they are a statistical outlier when compared to other judges, or disquieted to discover that their nuanced decisions are actually far more predictable than they would like to think.
But, for better or for worse, it seems that these judicial analytics platforms are here to stay. These platforms have been warmly embraced by top lawyers around the country, who view them as an innovative new tool to give their case that needed extra edge. Many predict that, in coming years, these tools may come to be considered a foundational component of litigation.