Intelligent Review Technology Results in Proven Cost-Savings

The ediscovery landscape is proving to be more treacherous given the rise of data proliferation and the increase in sanctions for mismanaging ESI. As the courts grow increasingly intolerant of discovery failures, litigants are faced with two choices: work harder by investing more resources to ensure thorough review, or work smarter by leveraging fewer resources with cutting-edge technology to achieve superior results. Dynamic companies know the latter is always the best option, and for them, the next generation of ediscovery technology has arrived.

Intelligent Review Technology (IRT) combines the best of both worlds by delivering the discerning analytics of a human review team in an automated platform capable of increased processing speed, consistency and accuracy. Although IRT encompasses many different technologies that can work independently or conjunctively to varying degrees, workflow automation, supervised learning and statistical quality control are the cornerstone features of an effective IRT system that together allow review to be conducted faster, more efficiently and accurately than even the best human review teams equipped with current discovery technology.

IRT learns while you work, and empowers the defensibility of your arguments with transparent reports and real-time metrics. By analyzing decisions made by lawyers, the system applies human logic to identify likely responsive documents and make categorization suggestions. IRT integrates human input with smart technology, reduces costs by 50%, and improves the quality and defensibility of document review.

The technology inside, Ontrack® Inview™, has three components:

• Workflow: Get the right documents to the right people. Workflow is an automated means to distribute and check in documents.
• Prioritization: See the most important documents first. Prioritization evaluates reviewer decisions to identify and elevate documents that are most likely responsive, enabling reviewers to view the most relevant documents first.
• Categorization: Harness the power of technology to learn from human decisions.  Categorization analyzes reviewer decisions and applies logic to suggest categories for the documents not yet reviewed