The advice@kCura Blog

Relativity Assisted Review in Relativity 8 includes enhancements that provide an easier, more flexible workflow and additional statistical insight into your projects. Among these improvements is the introduction of two new round types: pre-coded seeds and a control set.

These round types were added to improve the efficiency of document review for an Assisted Review project. Additionally, we wanted to include an accurate way to calculate the statistical measurements that are emerging as common metrics for judging the accuracy of a computer-assisted review process.

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Shimmy Messing

In this installment of his interview series, Jay Leib—resident computer-assisted review expert at kCura—interviews Shimmy Messing of Responsive Data Solutions about the Best in Service partner’s extensive experience using Relativity Assisted Review. Shimmy is Responsive Data’s director of technology and co-founded the company more than six years ago.

Jay: Tell us a little bit about yourself and Responsive Data.

Shimmy: I started Responsive Data with three partners in 2007. Coming from past experience in litigation support, our goal was to build an organization that’s client-focused and proactive. We help our clients with both paper and electronic discovery, printing, trial prep, and everything in between—the whole discovery lifecycle. I’m our director of technology, managing our internal infrastructure and our client-facing software. We have a Relativity team, an IT team, and few others that fall under my wing.

Tell us about your early experiences with Assisted Review.

We started using Assisted Review back in 2011. We dove right in, as we were confident in the technology behind Relativity Analytics and Assisted Review.  One of our earlier projects was more than 7 million records, and we learned a lot about optimizing our infrastructure, building a better index, understanding which types of data are best for an Assisted Review project, and more.

One key takeaway from those early projects was recognizing that we needed to be more selective about documents that have minimal text. The four corners rule—which emphasizes coding a document based only on the text within the four corners of a page, as opposed to its family members or custodians—helped guide that decision-making process a lot, and helped teach us how to recognize the content richness of a document.

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Importing Productions in Relativity with Natives

This recipe will show you how to set up your workspaces to support the import of productions with natives, when natives are available. This conserves disk space by storing only one copy of the images and the natives.

Download this recipe (PDF).

Mass Importing into a File Field

This recipe will show you how to upload multiple documents into a file field stored on a custom object.

Download this recipe (PDF).

Several members of our advice@kCura team are experts in custom development, helping our partners and clients build applications and integrations to extend Relativity’s functionality. To highlight some of the unique ways our users are taking advantage of the platform, we interviewed a few of our partners and clients who have worked with custom development to help create some more complex applications.

We sat down with Nancy Tassi, director of Relativity e-discovery services at Kensium Legal. In addition to Compendium Bridge, which integrates with Relativity, the technology solutions provider recently launched a new Relativity application—Compendium Dynamic User Provisioning—that’s available to anyone with a Relativity license.

If you have any questions about working with our team or have any custom development needs, please feel free to reach out to us at advice@kcura.com.

kCura: Tell us a little about Compendium Dynamic User Provisioning, and how you came up with the concept.

Nancy Tassi: After we integrated Compendium Bridge with Relativity, we looked for other needs that weren’t currently met by other applications in the Relativity Ecosystem. To do this, we initiated an open dialogue with our clients and our CTO, and we shared our thoughts with the Shana Kirchner and the kCura team. Through these conversations, we identified a valuable area for development: an additional layer of security that allows a hosting provider to give clients control over users and permissions, without granting them full administrative rights. We decided to build an application as a custom page in Relativity that allows hosting providers to give their clients this level of control.

When a law firm or corporation needs to create a new user, they typically call their hosting provider to make that request. With Compendium Dynamic User Provisioning, the provider can allow them to create a user without unlocking everything that’s associated with admin-level privileges.

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As the use of text analytics gains popularity in e-discovery, the need for skilled analytics administrators has grown significantly. To help our users validate their expertise with Relativity’s suite of analytics features, our certification team now provides the Relativity Analytics Expert certification.

When they began building the Analytics Expert program, the certification team reached out to advice@kCura to provide real world scenarios that would help them design both the written and practical portions of the exam. Preparing the exam was a long and interesting project, and we’d like to provide some insight into how it all came together.

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Please note that this post discusses topics from the Sedona Conference Institute’s annual program in late March. The conference was attended by advice@kCura team member Constantine Pappas, licensed attorney and computer-assisted review expert. Panels at the Sedona Conference are subject to a “no attribution rule,” which prohibits attendees from quoting a panelist by name.

During the Sedona Conference Institute’s 7th Annual e-Discovery Program in San Diego, computer-assisted review was a hot topic on several panels. We were inspired to take some of what we heard there and compile a post that takes a deeper look at this issue from the attorney’s perspective.

Computer-assisted review is still a relatively new tool in the legal community, and it’s often held to higher levels of scrutiny than traditional forms of search and review. This has led to discussions of how computer-assisted review will change the strategy and transparency of the e-discovery process. Based on what we heard at the Sedona Conference, we want to highlight three transparency concerns that might be most relevant for our users.

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Finding Conversational Uses of Phone or Fax with Regular Expressions

Using a regular expression and dtSearch, this recipe will show you how to find the words “fax” or “phone” when they are not followed by contact numbers.

Download this recipe (PDF).

Understanding the Statistical Sampling Formula

This recipe will break down the formula used to calculate the number of documents in a random sample set. You can reference this formula to ensure your random sample set is statistically valid.

Download this recipe (PDF).

Bruce Blank

In this installment of his interview series, Jay Leib—resident computer-assisted review expert at kCura—discusses best practices for rolling out computer-assisted review technology firm-wide with Bruce Blank, director of litigation support at Foley & Lardner LLP. Bruce has been with Foley & Lardner for more than a decade.

Jay Leib: What is your role at Foley & Lardner?

Bruce: I’m the director of litigation support, so I am responsible for all support and services for our litigating attorneys. I lead groups that perform court docketing, calendaring, and consulting for our case teams. I also support our litigation technology, both by ensuring we’re running a state-of-the-art setup and by training our attorneys in the software.

Your firm has been using Relativity Assisted Review for a while. How did you decide to start leveraging this workflow?

Our first push to implement the Assisted Review workflow resulted from reading an article in The New York Times. It came out a couple of years ago—you’re probably familiar with it—and it blew open the computer-assisted review process. We can look back and point to it, and see how it kickstarted a revolution in this industry by spurring a conversation among attorneys who started asking the questions we were all waiting for. We’d been leveraging Relativity Analytics since its inception, but we just hadn’t had the opportunity to put the computer-assisted review workflow to work. But when that article came out, our attorneys started coming to my team and asking if we could use that technology for them. Of course, we were happy to do it.

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During our live Ask the Doctor webinar in February—hosted by Dr. David Grossman and Jay Leib—attendees asked questions about the workflow, technology, and statistics behind Relativity Assisted Review. To keep the conversation going, we’ve assembled answers for some of the submitted questions we didn’t have time to address during the live event.

For more information about the statistics behind Assisted Review, check out our stats webinar and the white paper that accompanied Dr. Grossman’s statistical validation of Assisted Review. You can also explore the Assisted Review page for additional resources. As always, feel free to contact us if you have any questions.

Q: After your computer-assisted review project is complete, how do you efficiently pull in family members for coding consistency checks prior to producing—without having to run a full review of responsive documents and their families?

To start, this question implies that the review team may not manually review all of the documents categorized as responsive. To level-set, the decision to review or not review categorized responsive documents and/or their family members rests with the review team.

If the review team decides to review the categorized responsive documents, then Relativity has a variety of features to make this an efficient process. A team can go about the manual review as they normally would—with some added insight into the likely responsiveness of the documents at hand.

Pulling in family members for additional review or production tasks is also a frequent exercise for linear review, and it often comes up during a privilege review. Running a saved search and including family—or creating a view of your results and including families—will provide an interface to review family members of categorized responsive documents.

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Creating Hyperlinks to Shared Network Documents

This recipe will show you how to create a field that will contain a shared network document path that can be opened in the core reviewer interface via a hyperlink.

Download this recipe (PDF).

Using Reviewed Documents to Prioritize New Documents via Analytics

Using Relativity’s similar documents functionality, this recipe will show you how to leverage previously coded documents to determine the potential values of new documents in your workspace.

Download this recipe (PDF).