Legal landscapes are evolving rapidly, and one of the most significant disruptors in today’s law firms is the use of predictive analytics to analyze the extensive volumes of data that lawyers, particularly litigators, must sort through. There are two main fields within litigation that are particularly affected by predictive analytics: case law research and ediscovery. Artificial intelligence (AI) programs are heralded as the technology that will transform the way research and discovery processes are handled, and many startup companies are pinning their futures on the belief that the development of AI and its application in the legal setting will continue to catch on with lawyers and firms, bringing clients their way. Here are 10 companies using predictive analytics, including AI, to improve the way legal work is done in 2018.
If you are looking for a legal services startup that’s truly unique, look no further than Intraspexion, the company using deep learning and predictive analytics to predict and prevent potential litigation (through their own patented software system) – before it happens.
Intraspexion founder Nick Brestoff describes it as an early warning system that operates through analysis of a company’s emails to identify those that contain risk factors. For an easy example, Intraspexion, when properly used, could flag an inter-company email that contains text-patterns that might indicate sexual harassment or discrimination is taking place.
The AI behind the product allows companies to customize the software to account for company culture, and to constantly evolve to better spot potential issues as usage increases.
DISCO (CS Disco Inc.) is using predictive analytics processes to change the way law firms conduct e-discovery.
More than a third of the AmLaw 200 firms currently utilize DISCO’s legal technology to automate tasks and conduct large-volume document review.
The AI software combines speed and ease of use, plus its advanced workflow allows lawyers to front-load flagged documents so that they can be reviewed and identified first, making the firm’s e-discovery more efficient.
Visual learners will rejoice after a peek at Brainspace’s interactive visualizations, which are at once simple yet powerful.
By harnessing advanced machine learning with intuitive semantic technology, the company’s software is continuously learning how to better serve the law firms, corporations, and government entities that use it on a daily basis.
Whether used to automate workflows, or make sense out of increasingly voluminous discovery documents, the software integrates with other leading e-discovery platforms and management software. The announcement of their newest iteration of the software, Brainspace 6, came out on September 21, 2017.
A venture-funded startup that originated in 2012, Ravel Law just recently sold itself to legal industry powerhouse LexisNexis.
Lawyers and law firms can rightfully expect great things out of this partnership.
Ravel Law has previously carved out a name for itself as the company that seeks to (painlessly) turn every lawyer into a de facto data scientist through user-friendly data mining that can uncover patterns in everything from judges’ rulings to state case outcomes.
Now, by partnering with one of the biggest names in legal research, Ravel Law’s reach is extended that much further.
Speaking of LexisNexis companies, Lex Machina is another forerunner in the predictive analysis market.
With such notable and high-profile customers as Akin Gump, Ford, Holland & Knight, and Samsung, it’s no wonder Lex Machina is doing well for itself these days.
The company targets corporate legal departments within outside companies as well as law firms.
By mining and analyzing data from past lawsuits, it reveals connections and makes predictions about judges, lawyers, parties, and even the subjects of the lawsuits. It also helps legal departments select and manage outside counsel.
As its name suggests, LexPredict is a company focusing on, among many things, predictive technology for legal users.
It develops data products and services, including cloud-based APIs designed to address the gaps in users’ needs.
ContraxSuite, one of its most popular products, uses AI and human input to augment and integrate the user’s experience with the documents they are working with.
What else sets LexPredict and ContraxSuite apart from others? ContraxSuite is an open-source program, allowing users to audit and improve its code.
Touting itself as the world’s largest litigation database, with more than 40,000 cases added daily in the U.S. alone, Premonition is designed to help legal departments and claims managers pick their lawyer based upon performance in the courtroom.
This disrupts the traditional models of choosing an attorney, which usually rely on anecdotes, advertising, or, at best, the use of firm credentials as a proxy for litigation skills.
Premonition’s data-driven model has been featured in Forbes, The Miami Herald, the International In-House Counsel Journal, and many other publications.
As the recipient of Legaltech News’ Innovations Award for Best Legal Research Product, you would be right to expect something spectacular from Docket Alarm.
Although its basic premise is simple – never having to manually check for updates on a case’s docket again, thanks to preset alerts on new court activity – Docket Alarm’s offerings have progressed further than that, thanks to predictive analytics technology and a vast, accrued database of court filings.
As Docket Alarm is quick to point out on their homepage, the law is more than just judicial opinions. And with the web portal and smartphone app offerings, users can quickly and easily track and analyze full court records on tens of thousands of cases in federal, bankruptcy, and even intellectual property specialty courts.
Everlaw uses powerful predictive coding to sort through thousands of documents at a lawyer’s disposal and pull out the ones which are relevant to the search at hand.
The extensive user controls allow lawyers and paralegals to narrow their results by predictive ranges – e.g., search results with a predicted relevance rate of 60%, 75%, or any percentage the user chooses.
This gives Everlaw customers an incredible control over the end product in discovery and allows them to widen or narrow the funnel through which documents come through that are human-reviewed as a second step.
Data growth in the legal field especially impacts e-discovery, and to many firms, it seems that every year their cases contain an alarmingly greater volume of e-discovery to sort through. They’re not wrong.
E-discovery has become unwieldy and unpredictable in the face of the exponential growth of data points as technology advances, but Proofpoint seeks to put it firmly back in check.
Through predictive analysis, the company is tackling the bottleneck problem of e-discovery by implementing processes that allow lawyers to safely omit the IT calls and import/export issues that consistently plague in-house and in-firm e-discovery work.
By working alongside its legal clients, Proofpoint is reducing the financial and time cost that typically accompanies e-discovery, while keeping the processes in the hands of lawyers instead of third-party vendors and reviewers.