Kroll Ontrack Updates E-Discovery Cloud Service
Kroll Ontrack updates its cloud-based e-discovery software to better enable internal document discovery
Storage and security specalist Kroll Ontrack has updated its cloud-based e-discovery service, which it launched a year ago.
The updated version is said to give companies and legal teams more control over processes that are often very tedious.
Kroll’s Verve e-discovery software as a service (SaaS) enables users to upload data, select processing criteria, conduct early data assessment and review, and manage production in a web-based interface.
The service gives businesses and law firms more control of e-discovery projects without requiring upfront purchase or maintenance of infrastructure, hardware or security, as is the case with conventional e-discovery software packages.
The Verve service is available on-demand for any size case, Kroll Ontrack Vice President of SaaS Products Ken Ewell said. A project can be created in minutes by uploading data to Kroll’s secure tier III data centres, he said.
“With access to the most scalable e-discovery technology in the industry – capable of processing an average of 800GB of electronic data per day with a single-day high of over 2TB – users have the ability to identify custodians, determine filtering options and select output within an intuitive interface,” Ewell said.
“Users can conduct EDA to winnow a data set by 85 percent or more and sort data using the following tools: visual analytics, email threading, topic grouping, concept searching, near duplicate detection and near duplicate document comparison.”
Once users are ready for review, they can control the movement of data into the Verve review platform, which is based Kroll Ontrack Inview. Within the review platform, users can use industry-leading Intelligent Review Technology, which automates aspects of the document review process to increase review quality and efficiency.
Verve’s subscription pricing model provides predictable monthly discovery spending or an on-demand pricing model for project-by-project application.