The more documents a case involves, the more difficult the task for litigation teams to review and make sense of them. These days, even routine cases can involve many thousands of documents, while more complex cases can involve many millions. For litigators, these mountains of documents present a challenge: How to uncover the stories the documents contain so that you can prepare your cases for discovery and trial — and do so within the limits of available time and budgets.
This Thursday, Aug. 27, a free webinar will demonstrate how litigators can address these challenges using sophisticated analytics tools. The webinar, “Litigation Analytics: How to Find Information Critical to Your Case,” will show how analytics tools can turn mountains of documents into molehills, enabling litigators to quickly and affordably zero in on what they need to know. Continue reading
When a large banking institution filed suit alleging accounting fraud caused it to lose millions from a bad loan, the litigation was sure to turn nasty. Soon enough, the bank faced a major production request from defendants. Even after culling, it had 2.1 million documents to review, with limited time and budget to waste.
The bank turned to Insight Predict, Catalyst’s unique Technology Assisted Review platform. Its plan was to employ Predict’s Continuous Active Learning protocol and see if TAR could be effective in further reducing the population. The result: The bank was able to achieve 98% recall after reviewing just 6.4% of the population. Continue reading
Last February, we reported here on a proposed ethics opinion from the State Bar of California that would require lawyers who represent clients in litigation either to be competent in e-discovery or associate with others who are competent. At that point, the bar was accepting public comments on the proposed opinion in advance of issuing a final opinion.
Now, that opinion has been finalized and was issued on June 30 as Formal Opinion No. 2015-193. The final opinion largely mirrors the proposed opinion, with only minimal changes. As before, the opinion says that attorneys have a duty to maintain the skills necessary to integrate legal rules and procedures with “ever-changing technology.” In support of that statement, it cites the American Bar Association’s 2012 amendment to the Model Rules that discussed the duty of lawyers to keep abreast of changes in the law, “including the benefits and risks associated with relevant technology.” Continue reading
E-discovery review has come a long way in a short time. Not long ago, manual, linear review was the norm. Then came keyword search, which helped increase efficiency but was imperfect in its results. Technology-assisted review was a great leap forward, but early TAR 1.0 versions were rigid and slow. Only with the arrival of TAR 2.0 and Continuous Active Learning did TAR finally save the day for e-discovery.
The brief history of how TAR evolved is depicted in a new Catalyst infographic, A TAR is Born: The Making of a Superstar. See how e-discovery review matured from a demanding infant to a Ph.D. in savings. After you check out the infographic, read much more about TAR in Catalyst’s free e-book, TAR for Smart People.
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In his 2015 opinion in Rio Tinto PLC v. Vale SA, Magistrate Judge Andrew Peck extolled the benefits of technology assisted review using Continuous Active Learning. In particular, he noted that CAL reduces or even eliminates the need for the rigid seed set required by older TAR methods.
CAL’s flexibility on seed sets was illustrated in a case where a large banking institution alleged it lost millions due to a borrower’s accounting fraud. In response to the borrower’s production request, the bank faced review of 2.1 million documents, even after culling. With neither the time nor budget to review them all, the bank turned to Catalyst’s Insight Predict, the first commercial TAR engine to use CAL. Predict cut the review by 94%.
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Erin Harrison, editor-in-chief, Legaltech News; John Tredennick, founder and CEO, Catalyst; Jeremy Pickens, senior applied research scientist, Catalyst; and Tom Larranaga, publisher, Legaltech News, at the awards ceremony.
We are thrilled to announce that at a ceremony last night in San Francisco, Legaltech News named Insight Predict—Catalyst’s next-generation technology assisted review (TAR) product—as the winner in the New Product of the Year category of the Legaltech News Innovation Awards.
The award was announced at a special event at the City Club of San Francisco at the close of Legaltech West Coast.
The LTN Innovation Awards recognize the best legal technology leaders, products and projects in the legal community. Award winners were chosen by a panel of judges consisting of members of Legaltech News’ editorial staff. In addition to recognizing law department and law firm leaders, LTN presented awards to 20 vendors and services providers across a variety of categories.
With the February 2015 release of Catalyst’s Active Review functionality within Insight Predict, Catalyst became the first to integrate continuous active learning (CAL) technology—the next generation of TAR—directly into the review process. Active Review eliminates the traditional separation between linear review and TAR by combining them in a single, integrated workflow. Continue reading
In the annals of case law about e-discovery and technology assisted review (TAR), Malone v. Kantner Ingredients will be only a footnote. In fact, were it not for a footnote, the case would barely warrant mention here.
This blog has chronicled the increasing judicial acceptance of TAR, starting with U.S. Magistrate Judge Andrew J. Peck’s seminal 2012 opinion in Da Silva Moore v. Publicis Groupe, which was the first to approve TAR, and continuing through to Judge Peck’s recent opinion in Rio Tinto PLC v. Vale SA, which declared, “the case law has developed to the point that it is now black letter law that where the producing party wants to utilize TAR for document review, courts will permit it.” Continue reading
With 2015 already half over, we thought it would be interesting to look back at which were our most popular posts on this blog. These are the posts that received the most traffic during the first six months of the year, regardless of the year the posts were originally published.
As you can see, there is great interest among our readers in a simple but vexing question: How many documents are in a gigabyte? Two posts on that topic by Catalyst’s CEO John Tredennick are persistently among our most popular, as is a third on how many bytes in a gigabyte. And stay tuned, because John has been promising still another update with new information.
Other popular topics included technology assisted review, privilege logs, e-discovery costs and e-discovery ethics. Continue reading
U.S. Magistrate Judge Andrew J. Peck — author of the first-ever court decision approving the use of technology assisted review in e-discovery — was recently a guest on the Legal Talk Network podcast Digital Detectives. Hosts Sharon D. Nelson and John W. Simek, president and vice president of Sensei Enterprises, interviewed Judge Peck about how TAR works, what cases it is suitable for, and how it is being accepted in the courts.
Given Judge Peck’s leadership in broadening the adoption of TAR, we thought his comments would be of interest to readers of this blog. With the gracious permission of Sharon, John and the Legal Talk Network, below is a partial transcript of the show highlighting Judge Peck’s comments on TAR. You can hear the entire program through the Soundcloud player above or at the Legal Talk Network. Continue reading
When e-discovery goes international, it gets even more complex and costly. But technology assisted review can be as effective in reducing costs for multi-language, multinational matters as it is for matters here in the U.S.
This infographic illustrates how Catalyst Insight Predict helped streamline a recent patent litigation for a Japanese client. See how Predict’s Continuous Active Learning improved results and cut the time and cost of review by over 85%.
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