Lawyers relying on legal analytics
decisions for years. He looks at nearly 100 variables — like determining an appellate court’s basis for reviewing a case.
Current artificial intelligence tools are not yet as detailed as his own database, he says.
But the new analytics are still a big advance over manual work, proponents say.
Previously, tracking down insights on judges and opponents was “super slow — to the point where you wouldn’t even do it,” said Nguyen, who served on Lex Machina’s advisory board from 2012 to 2015 and is now a lawyer at Haynes and Boone LLP. “It would just cost so much money.”
The legal research behemoth LexisNexis announced last month it would acquire Ravel Law, and it also bought Lex Machina; neither Ravel Law nor Lex Maxina would disclose the purchase prices.
Jeff Pfeifer, LexisNexis’ vice president of product management, says inhouse lawyers at companies are particularly interested in data analytics as companies look to tighten spending. Law firms are rapidly adopting the tools, too.
Legal technology is “at the beginning edge of a rapid tipping point,” Pfeifer said.
Lex Machina was founded in 2006 as a public interest project of Stanford’s law school and computer science department; it spun out in 2010 as the first legal analytics company of its kind, according to founder and Stanford Law Professor Mark Lemley.
“You know when you’re in Silicon Valley when the law schools are starting companies,” he said.
Its initial focus was intellectual property. The company is now expanding its offerings to other areas: It launched an employment litigation module on Thursday, following an expansion into commercial litigation data in late June. Lex Machina says its customers include more than half of the country’s largest law firms. The company declined to say how much its software costs.
Another San Francisco company, Judicata, founded in 2012, started offering legal analytics tools to clients in June. It has a team of in-house lawyers who work side by side with engineers to increase accuracy, according to co-founder and CEO Itai Gurari.
Judge Alex Kozinski of the U.S. Court of Appeals for the Ninth Circuit said he is “not so troubled” about the implications of legal analytics for forum shopping — a well-established strategy in which lawyers file a case in a specific court because of its reputation of ruling for similar plaintiffs.
“Lawyers have always tried to figure out what judges will do in current cases based on past cases,” he said. “It’s not any different than it was before, just done mechanically.”
Legal analytics tools can partially level the playing field between novice and senior lawyers, some say. “A lawyer that’s three years out of law school can now know more about a judge, opposing counsel or party than a lawyer who’s been practicing in the area for 25 years,” Byrd said.
It can also help lawyers land clients: Being able to quantify the chances of winning or losing a case makes clients more willing to sign on. “They can go to prospective clients and say, ‘Our firm is different from other firms,’ ” said Nik Reed, co-founder and chief operating officer of Ravel Law. “‘We’re not going to waste your money because we now have this data to support our decision making.’ ”
Chris Mammen, a patent litigator at Hogan Lovells LLP, who has used Lex Machina for nearly a decade, said that data analytics can help show how long an opponent tends to litigate a case.
Owen Byrd, Lex Machina’s chief evangelist and general counsel, compares the possibilities created by the new field to Moneyball, the 2004 Michael Lewis book about the Oakland A’s pioneering uses of data analytics.
“Lawyers, just like baseball players, still have to have the core skills of the profession,” Byrd said. “But those skills can now be supplemented.”