The Secret Weapon for eDiscovery Success You Need to Know

Artificial intelligence has been at the forefront of eDiscovery software development,  automating processes and simplifying solutions, all to go above and beyond the clients’ changing needs.

Customers are able to optimize their cases and investigations through maximizing efficiency and productivity and minimizing security risks and costs with the different types of AI being used in eDiscovery.

Supervised vs Unsupervised Learning

The most common use of AI in eDiscovery can be categorized into two main subfields: supervised and unsupervised learning during early case assessment (ECA) and the review processes. 

Supervised Learning

Supervised learning requires software to be trained by a human through rounds and rounds of sample data sets to identify important documents. Once the software recognizes the patterns, it is able to continue the review process autonomously.

This technology is often referred to as TAR, or technology assisted review and has been integral to cutting down the time spent on ECA and review. 

Unsupervised Learning

Conversely, unsupervised learning does not need to be trained. The software is able to extract and group important documents based on similar topics, and refine its pattern recognition to actively yield better results. 

TAR’s younger sibling CAL, or continuous active learning, has been the newer, faster and stronger AI solution for eDiscovery. Because CAL is coded by reviewers unlike TAR, subject matter experts (SMEs) are able to use their time and resources on higher level tasks, increasing the overall efficiency of your legal office. 

eDiscovery providers are also utilizing conceptual searching (sometimes called conceptual clustering) to simplify the eDiscovery process. Conceptual searching is another example of unsupervised learning. The software uses a machine learning algorithm to decipher documents, seek out keywords and cluster the documents into categories based on their topics. 

Using these three forms of AIML, eDiscovery providers create a streamlined and easy-to-use eDiscovery platform for their clients. 

Here are six of the most valuable benefits that AI in eDiscovery services have to offer our clients. 

  • Faster Processing Capabilities

AIML algorithms, like the aforementioned TAR, CAL and conceptual search, significantly cut down the time spent on ECA and review processes. With automation, you’re able to review documents at 10x the speed. 

  • Incredible Accuracy

Predictive coding provides users with a richer batch of relevant documents by effectively eliminating irrelevant information and clustering together similar pieces of data.

  • Risk Reduction

AI improves your data security through the use of protective automated services. The software can be used to find and redact personal information during the review process.  

  • Saving You Money 

The automation of review and ECA processes reduces eDiscovery costs by lessening billable hours for your customers. 

  • Clear Data Analysis 

Conceptual search is often followed by an AI-powered, interactive and user friendly visual aid to consolidate categorized data. 

Productivity You Can’t Beat

AI can be used to determine the best time of day to process your review, apply software enhancements and system updates so you can be the most productive. 

The greatest quality of AI in eDiscovery software is its constant evolution to stay up-to-date with the changing demands of the legal industry. Whether it’s coded by a human or self-improving with autonomous algorithms, AI has got what it takes to keep you performing at your best. 

Venio Systems offers one of the best end-to-end eDiscovery software with AI-powered review to perfect the automation process to be 10x faster, create 90% less data to review and increase your team productivity tenfold. Don’t believe us? Request a demo to try our software for yourself!

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