Powerful EDiscovery Analytics: Utilizing Cluster Wheel Visualization, Concept Searching, & More

Data analytics can play a huge part in reducing the overall size, time, and cost of a review project. When applied effectively, analytics not only help identify relevant data sets more efficiently but also aid in culling down data to a manageable size. With today’s evolving tech landscape , eDiscovery analytics tend to be powered by machine learning and AI technology.

When applied during eDiscovery, analytics workflows can range from cluster analysis to predictive coding and data sampling, with each adding its own value to a reviewers toolkit. One common provider for eDiscovery analytics is Brainspace. Brainspace by Reveal is a premier tool that allows for in-depth visualization, analysis, and navigation of ESI in a secure environment and scalable format.

Within Brainspace, users have access to an interactive dashboard that houses various helpful features and benefits including:

• Cluster Wheel Visualization
  • Visualize the data
  • Browse data in an organized manner
  • Browse data at scale
  • Interact with the data
  • Concept identification through cluster analysis
• Communication Analysis
  • Analyze communication patterns
  • Explore communication timelines
  • Identify relevant topics quicker
• Concept Searching
  • Search by keywords, phrases, or concepts while excluding irrelevant hits
• Metadata Dashboard
  • Tagged & searchable elements
  • Filter & cull data
  • Comprehensive metadata documentation
• Thread Analysis
  • Email threading visualization
  • Identify level of involvement within a conversion
• Supervised Machine Learning
  • Continuous Multimodal Learning (CMML)
  • Predictive coding
  • Intelligent sampling

By utilizing technology assisted review and continuous active learning, legal teams can build defensible and repeatable workflows that have the ability to be applied at scale to data intensive matters.

Learn more about the Brainspace at https://brainspace.revealdata.com/about