What Admins Look For When Choosing An eDiscovery Platform

A lot of platforms boast “robust features and analytics,” but how do they really stand out from the rest?

electronic discovery ediscovery forensic big data analytics analysisHaving managed several large eDiscovery projects, I know that choosing the wrong review platform can have devastating consequences to your case. The problems are not always apparent up front – it’s when you get three to four months into the document review that you realize that you have made a mistake. By then, it’s too much of a hassle to get out of your contract, find a new provider, and transfer data to a new provider. Casepoint is an eDiscovery platform that has been around for about a decade and has seen continuous evolution since its inception.

A lot of platforms boast “robust features and analytics,” but how do they really stand out from the rest? How do you know which platform you should bet your case and your client’s money on? Here are some of the top reasons why Casepoint solves some of the biggest eDiscovery administrator headaches.

All-in-One Platform

Sometimes, the biggest hiccups come when trying to make one system compatible with another as you move through the eDiscovery process, or when you and your team need to learn two or three pieces of software in order to complete an eDiscovery project. Casepoint eliminates those headaches by putting everything you need in one tool. In addition to early case assessment tools, Casepoint has tools for cloud collection, data ingestion, review (with technology assisted review and advanced analytics), and production. Less moving pieces also means less waiting on other vendors to complete their portion of a task as you sit idly.

Another problem that I have found is that when you have more cooks in the kitchen, when something goes wrong, everyone points their fingers at everyone else. For example, one time, I was working on a case and we had received a batch of documents that had about 3,000 documents, but the load file listed about 5,000. Some of the files were corrupt and did not copy somehow. When this was finally noticed months later, the team who processed the batches for production said it wasn’t their fault, it was the fault of the team that collected the data. That team said they are not responsible for quality control of the production and load files. It was a mess. With one team offering support for all aspects, no one is throwing anyone under the bus or pointing fingers and problems get solved faster.

They Own the Software and the Servers

For those unfamiliar with the way 99% of eDiscovery companies work, here’s a breakdown. If you want to use say, Relativity, you don’t call up kCura, the maker of Relativity, and ask for a quote. You find an authorized provider, who sells you data storage and licenses to Relativity, which they get from kCura. It’s like when you want a pair of Nikes, you don’t go to Nike headquarters and ask for shoes, you go to Famous Footwear or some other shoe store, who marks up the wholesale costs to sell at retail, so that both they and Nike can make a profit from you.

That’s not how Casepoint works. If you want to use Casepoint, you call Casepoint and use their software on their servers. They do not charge licensing fees because they are not licensing the software. They own it. Some eDiscovery providers will force you into a yearlong contract for licensing fees. Then, if a case ends in one month, or 13 months, you are wasting a lot of money licensing software that you don’t need anymore. Casepoint owns the software, so they don’t need to pass on licensing fees to you.

Similarly, a lot of eDiscovery providers use Amazon Web Services (AWS) servers to host your data, which is mostly fine most of the time. For those with short memories though, Google can help.

aws

Just a few months ago, AWS went down, taking large portions of the internet down with it. Casepoint uses their own farms of servers. Owning the software and the servers makes it easier for them to roll out improvements. If there is a feature that users want, they do not have to go through 20 middlemen to report bugs or add new features. This also makes Casepoint a lot faster. Doing things like creating batches, running analytics, or performing searches is much faster on Casepoint’s servers than when using leased servers because they have tight control over the infrastructure and can put the resources into speed. One time, I was using Concordance and accidentally hit a column header to sort documents by date instead of Beginning Bates Number, a process that could not be halted. It took fifteen minutes to complete. Being able to have even minor speed improvements on simple searches can save dozens of hours over the course of a project.

Tools on Par with the Big Boys

Running keyword searches can be a good way to quickly identify hot docs, but it will never cast just the right net – it’s either going to be under-inclusive or over-inclusive and waste time and let hot documents slip through the cracks. What technology-assisted review (TAR) does is look at patterns in documents that you have coded to find patterns in documents to identify documents with a high probability of being hot and documents with a high probability of being irrelevant. CaseAssist, Casepoint’s latest machine-learning analytics tool, analyzes your data and suggests documents for you to review. It works in the background so as new documents are coded, and you can wake up to an email from CaseAssist with documents that it found overnight. As more documents are reviewed, the process fine-tunes itself.

Casepoint also has the analytic tools that you find in some of the mainstream eDiscovery platforms, from deduping and finding similar documents and email threading. When you batch out assignments, and one draft of a purchase sale agreement appears 100 times, you can use these tools to quickly and uniformly code each instance without having each of your coders find one in their batches and have a dozen people read the same document once, and then another 10-15 times as they compare drafts of the same document to make sure they are all still the same.

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Casepoint also has tools to let you view coder progress and track how the batches are progressing:

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It has built-in data visualization tools for filtering. Here is an example of a graphic representation of dates of emails with sliders at the bottom to narrow your search filters:

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Here are more data visualization tools to sort documents by email sender domain:

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Word clouds, to get an overview of your data and to see the relationship between data sets:

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Conclusion

In short, Casepoint’s got the features you need and the infrastructure you probably didn’t think to ask about.


Jeff Bennion is a solo practitioner at the Law Office of Jeff Bennion. He serves as a member of the Board of Directors of San Diego’s plaintiffs’ trial lawyers association, Consumer Attorneys of San Diego. He is also the Education Chair and Executive Committee member of the State Bar of California’s Law Practice Management and Technology section. He is a member of the Advisory Council and instructor at UCSD’s Litigation Technology Management program. His opinions are his own. Follow him on Twitter here or on Facebook here, or contact him by email at jeff@trial.technology.