MCS is proud to be a Blue-level Relativity Best in Service partner. As a leading eDiscovery service provider, MCS has integrated the Relativity eDiscovery platform to deliver feature-rich capabilities for web-based document review and analysis.
Through a voluntary audit, MCS demonstrated expertise and experience with hosting projects in Relativity to earn Best in Service status. Relativity evaluates Best in Service partners’ individual data centers based on technical infrastructure, customer service and product knowledge. Additional criteria include duration as a hosting partner, size of Relativity installation and core Relativity certifications. By partnering with MCS, clients have access to Relativity in an environment that continuously exceeds system performance and service delivery standards. All projects are managed by Relativity-certified and industry-certified consultants with over 15 years of electronic discovery experience.
Relativity's structural analytics, conceptual analytics and assisted review play an important role in the development of MCS's intelligent review workflow. With the expertise of MCS's dedicated support team and Relativity's advanced technology, you will receive the best review workflow customization in the industry.
Relativity's Structural Analytics allows us to quickly assess and organize a large, unfamiliar set of documents. You can either batch out these groups of documents for review or use them to create new document sets for further analysis. We are able to use these groups to run structured data operations to shorten review time, improve coding consistency, optimize batch set creation and improve your analytics indexes.
Relativity conceptual analytics uses an index to identify similar ideas or concepts within a document set, making the process faster and more efficient than matching specific search terms as done by traditional search engines.
With this program, MCS is able to perform the following searching techniques:
Relativity Assisted Review is a computer-assisted review workflow that combines process and technology to allow flexibility and document transparency. This statistical approach for auto-ranking responsiveness of documents is known as predictive coding.
Predictive Coding Workflow:
This program orders documents from the most responsive to the least responsive, and our team will analyze the percentage of responsive documents as well as the percentage of correctly coded documents to determine when the review is finished.
Active learning puts the most relevant documents in your reviewers’ hands—fast. It does this by continually learning, in real time, from your team’s coding decisions and using those decisions to deliver the documents that matter most.
Relativity AL keeps tabs on coding decisions in real time to refine its understanding of what’s responsive. As your project progresses and reviewers code more documents, the engine gets smarter, analyzing the coding decisions and constantly refining its understanding of what’s most important to your matter—so you can get to the relevant information faster. It can also be combined with other analytics tools to enhance the review. For instance, running email threading to eliminate non-inclusive emails and duplicate spares, then running Active Learning on what's left.
Read more about Active Learning and Artificial Intelligence in document review in our blog post here.