Back-to-Back: Lineal Wins the Relativity Innovation Award for Best Innovation Solution Provider
Lineal, a global legal data services and technology company leveraging AI and process-driven workflows for law firms and corporations, has, for the second year in a row, been awarded the 2022 Relativity Best Innovation Solution Provider Award for their AI suite of Relativity enhancements. The results were announced during Relativity Fest on October 27th.
Each year Relativity recognizes organizations and individuals who build innovative solutions, break down barriers for technology in the practice of law, move eDiscovery forward, and take Relativity to the next level. Winners in the technology categories are organizations using the Relativity platform in creative ways—solving difficult or unique challenges within and outside of eDiscovery.
“Lineal’s clients are the force that drives our innovation, partnering with us to design solutions to their most pressing discovery problems,” said Damon Goduto, Partner at Lineal. “Achieving this honor two years in a row energizes us to work harder and partner greater as we strive to achieve our mission of reshaping the litigation services space.”
Relativity specifically recognized Lineal for its AI-enabled applications Lineal Amplify and Lineal Images, applications that empower litigators and corporate in-house teams to visualize their data, repurpose workflows, speed evidence retrieval, and accelerate the discovery process.
Lineal’s full application suite includes:
Amplify – A Relativity workflow automation tool which brings organization and structure to the chaos of modern litigation by providing a framework for strategic decision-making on a single engagement or across a portfolio of matters. Amplify provides case teams to repurpose their processes and workflows across matters, supplies deep metrics at a glance, with automation and notifications built within.
Lineal Images – A Relativity integrated AI-powered review interface for viewing, classifying, and producing images and other graphics-based content in both SaaS (RelativityOne) and on-prem deployments. Lineal Images allows users to review images as tiles in logical groupings based on their content – landscapes, cityscapes, worksites, colors, etc. — and then tag those images and their duplicates.
Lineal PrivFinder (LPAi) – A proprietary privilege identification application built for Relativity, Lineal PrivFinder immediately identifies and scores privilege documents. LPAi begins by analyzing communication data (i.e., law firm domains, the role of the sender, keywords, etc.) and then inputs case-specific information (communications involving aligned and adverse parties and lawyers, in-house legal staff, and professional signatures, etc.) to provide the likelihood of a document being privileged. Next-generation AI machine learning is informed by a human expert to catch indicators of privilege with uncanny accuracy and continues to improve iteratively with subsequent use.
Lineal ChatCraft – A bespoke Lineal Relativity enablement tool, ChatCraft Enables users to tag and review chat data (Google Chat, Teams, Slack, SMS, etc.) on the per chat, per day, or even individual message level. ChatCraft allows users to keep track of important documents by associating attachments with conversations. Further, users can visualize chat history over timelines, revealing key trends in communications. As a result of ChatCraft, the production of collaborative data is substantially smoother, as the application allows you to export only the relevant messages without redacting countless other unresponsive messages.
Lineal ECAi/Bot Detection – Designed to eliminate junk and provide upfront logical culling. Bot detector technology identifies “bot” generated messages in the review database. This technology is not just a domain analysis; it also compares the ratio of sent messages by certain domains to the number of times those messages were replied to or forwarded, essentially identifying one-way communicators. ECAi culls, on average, an additional 15% of all communications docs. Additionally, ECAi identifies intense conversations through sentiment analysis, and communication patterns are brought to the surface.
Lineal Snippets – An exclusive Lineal Relativity application, Snippets provides a field within Relativity that displays keyword hits in context, enabling reviewers to code multiple documents at once without the necessity to open them fully.
Lineal Ai Threading Application (LTAi) – LTAi identifies the most inclusive document and delivers this information inside of Relativity. LTAi doubles standard suppression rates of communication documents (email, Slack, messages, Teams, etc.) compared to Relativity threading. The average culling performance with LTAi is approximately 30%.
Our story on Cision: https://www.prweb.com/releases/2022/11/prweb18994701.htm
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About Lineal – Lineal is a global legal data services organization leveraging AI and process-driven workflows to solve litigation, privacy, compliance, DSAR, information governance, and cyber issues for law firms and corporations. Headquartered in Dallas, and with offices throughout the North and South Americas, Europe, APAC and the Middle East, Lineal has been delivering pioneering solutions since 2009
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About Relativity – Relativity makes software to help users organize data, discover the truth and act on it. Its SaaS product RelativityOne manages large volumes of data and quickly identifies key issues during litigation and internal investigations. The AI-powered communication surveillance product, Relativity Trace proactively detects regulatory misconduct like insider trading, collusion and other non-compliant behavior. Relativity has more than 300,000 users in approximately 40 countries serving thousands of organizations globally primarily in legal, financial services and government sectors, including the U.S. Department of Justice and 198 of the Am Law 200. Relativity has been named one of Chicago’s Top Workplaces by the Chicago Tribune for 10 consecutive years. Please contact Relativity at sales@relativity.com or visit https://www.relativity.com for more information.