Stanford-Bred Startup Uses Moneyball Stats To Handicap Judges, Lawyers
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If you’re being sued for patent infringement before U.S. District Judge Lucy Koh in the heart of California’s Silicon Valley, there’s something you ought to know. Koh is tough on defendants and only grants 18% of motions for summary judgment, less than half the national average. So your lawyers had better be on their game before they try to convince Koh to chuck out the case, and you’d better have a fallback strategy in case she doesn’t.
These stats are just a sample of what a venture-funded startup with roots in a project funded by Cisco Systems CSCO -0.22% and Apple AAPL +0.13% is doing to bring mathematical analysis to the arcane world of litigation. Where Lexis and Westlaw tell attorneys what the law is, Lex Machina tells them what actually happens in the courtroom.
The system, focusing for now on the litigation-intense world of patent law, has compiled an exhaustive database of patent cases going back to 2000 so companies and lawyers can determine how many times a patent has been the subject of litigation and how the lawsuits were resolved. Lex Machina also handicaps law firms based on their win-loss records before specific judges with specific procedural maneuvers, so in-house attorneys can determine who to hire.
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