Electronic discovery or e-discovery refers to discovery in legal proceedings such as litigation or government investigations where the information sought is in electronic format. The ever increasing amount of litigation, greater volumes of data and a move toward adding in-house e-discovery capabilities require strong tools for e-discovery.
Data is scattered throughout companies and has become progressively more difficult to manage. Companies are dealing with big data, data in shared repositories such as Box.com, data on mobile devices, etc.
Data must be protected during e-discovery just as it does when it is a part of any other business activity. The degree of security risk depends on the nature of the data. Standard business contracts might not be highly sensitive and thus create minimal risk, but exposure of intellectual property that represents the crown jewels of a company could be a major risk.
When legal hold is used effectively, companies can meet their preservation duties, then do targeted collections as needed in the case. Good hold process plus targeted collections can significantly reduce the amount of information that must be reviewed by attorneys, which accounts for 70 percent of e-discovery costs.
Another value proposition in using an automated legal hold solution that is integrated with collections and first-pass review is the ability to re-purpose a collection.
Cloud offerings could be used to centralize all this data in one place for efficient reuse and risk management.
Several trends are contributing to strong growth in tools for the e-discovery. In addition to a group of large e-discovery vendors, many smaller vendors have products that are working well for their customers, and there is also room for new entrants that improve performance or address specific needs.
Each product has particular strengths, and that wide array offers options that can be used very selectively or in conjunction with each other to meet a company’s goals.
Sometimes, legal holds are required. Legal holds are required when a company might reasonably expect litigation and therefore should not delete information that might be relevant to the litigation.
Legal Hold Pro
This application has templates for the system and the database with the contact information for employees who are custodians of data. The system can also be used to track the information and people affected, automate the interviews with custodians, send reminders and release holds when appropriate. It allows to check the information of terminated employees to see if it might be subject to hold, and review responses from custodians to create the collection plan.
The same collection and review tagging could be used again by adding only the incremental data generated since the original one.
As a cloud product, Legal Hold Pro is quick and easy to launch, and is updated frequently.
Technology-assisted review (TAR)
Once a set of documents is located that may be responsive to the e-discovery request, it needs to be searched. The effective use of human skills in conjunction with computer capabilities is a key ingredient in lowering down the volume of data that needs to be reviewed by attorneys or other legal professionals.
Technology-assisted review (TAR), also called predictive coding, is a method for training a computer to spot documents that may be relevant and distinguish them from those that are not.
Catalyst
Catalyst provides e-discovery software and services.
Catalyst Insight is a secure cloud-based platform where clients can search, review, mark and produce documents. It can be augmented with Insight Predict, a predictive ranking TAR 2.0 solution that uses continuous active learning (CAL) to speed the review process by allowing technology to work alongside the judgments that human reviewers make. The solution brings the most relevant documents to the top of the list rather than working in a linear fashion.
The company’s TAR 2.0 software is specially designed for e-discovery. Some of the early TAR products were re-purposed machine learning tools. They can work in situations where the target documents are a large proportion of the total, but if you are looking for the one percent that are ‘hot docs,’ then they are not as effective. With TAR 2.0, attorneys and legal professionals who are subject matter experts do the initial coding for relevancy. Each of their judgments about the relevancy of a document is fed back to the system as a means of “training” to identify others that also might be relevant.
In the case of earlier versions of TAR, adding new documents caused the random sampling assumptions to no longer be correct. Unlike earlier products, which had a finite learning phase and then a production phase, TAR 2.0 allows new coding to be immediately incorporated into the algorithm for searching the document repository so that it is correctly tuned to the current problem domain.
It allows every decision made by an attorney to be put to maximum use, allowing humans to do what they do best, and then let the computer do what it does best, which is to quickly surface the relevant documents.
One practical limitation of early versions of TAR was that it could not handle small volumes of documents because the usual percentage of samples did not provide enough examples from which the computer could learn. This became improved in later versions of the tool.
Recommind
In 2006, the federal rules for discovery changed to include discovery of electronic information. E-discovery includes the collection, processing and analysis of e-mail and other electronic documents that might be relevant to a case, including determination of whether the documents are indeed relevant.
What sets Recommind apart from many industry solutions, is the ability to prioritize records and pull together similar records.
Recommind’s Axcelerate product can research, collate and assemble electronic records into reports. The electronic records for a single case can sometimes number into the millions.
Axcelerate’s adaptive batching expedites the feedback loop on search or analytics-based document sets, making continued batching not just automatic, but also conditional on the relevancy found through sampling. That enables a law firm to determine by batch if certain records are indeed relevant to a case, rather than reviewing them individually.
Magnum Software
It allows to quickly search, annotate and link to portions of documents. The collaboration capability is quite robust. Users can share their work product with any other users or groups of users via a one-click e-mail alert.
The alert automatically includes a direct link to the note and passage so the recipient can log in from anywhere, review the remarks and continue the discussion thread within Opus 2 Magnum. Additionally, multiple users can “chat” within the application.
The application works much better with smaller files than loading them all to a large database, but Magnum can also scale for larger file sizes.
Exterro
This in an excellent tool for eDiscovery. It provides eDiscovery and other records management needs in a single platform. Genome data mapping module can be added which will create an excellent solution for the data mapping.
With the increasing number of records and need to keep track of them and pull them together efficiently, the demand for KM technology for records and information management will continue to grow.
Galaxy Consulting has 17 years experience in ensuring that ediscovery process is going smoothly.
