We hear a lot of talk about “big data” and how it will drive law practice in the future. In theory, someday you will have every bit of relevant practice data at your fingertips and you will be able to use that to predict how a judge will rule on a case, have computers crunch through discovery, and realistically predict the cost of litigation. That someday is getting closer and closer, particularly with tools like Ravel.

At its most basic, Ravel allows you to visually map cases in a way that is arguably much more intuitive than KeyCite. Entering a case — or a Boolean or natural language search — will get you a visual map of circles, arrows, and lines. That map shows you at a glance which cases have been cited the most (those are the largest circles in the screenshot above), how in-depth the treatment of the cited case is (thicker the line, more in-depth the treatment), and allows to change the date range and jurisdictions on the fly.

At its most advanced, Ravel also offers judge analytics, where you can see patterns about how judges rule and what ideas and people influence those judges. That type of analysis could be incredibly helpful in making decisions about settlement, deciding who should argue a case, whether to strike a judge, and how to approach your pretrial motion practice.

Sounds great, right? Too bad you will not be able to afford it. The lowest cost plan is $1,800/year, unless you want a very basic free plan that only includes Supreme Court and Circuit Court cases. Oh, and you will pay even more for the judge analytics. That $1,800 price is likely outside the reach of most solo and small firm practitioners, which means that the Big Data edge will, at least at this point, go to BigLaw. Here’s hoping the cost comes down and we all get access to cool tools like this.

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