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Relativity amplifies your efforts with computer-assisted review.

Relativity Assisted Review is the flexible and transparent computer-assisted review workflow. By amplifying human expertise with powerful technology, Assisted Review serves as a better way to review large volumes of electronic information, reduces risk and cost, and is more accurate than traditional review methods.

Having Relativity Assisted Review's insight means we can provide better results for our clients by focusing our attention on relevant documents from the beginning of a case.
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Relativity Assisted Review

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How does Assisted Review work?

Assisted Review combines technology and process, allowing you to train Relativity on key issues by coding subsets of documents. It requires three main components—domain expertise, an analytics engine, and a method for validation.

Review teams begin by subjectively coding a sample set of documents. Based on those expert decisions, Relativity determines how the rest of the documents in a case should be marked. You then validate Relativity’s work by manually reviewing statistically relevant subsets of documents to ensure coding accuracy.

Because batches of documents categorized by Relativity are validated using statistics, you can be confident in your results.

 

What are the benefits of Relativity Assisted Review?

  • Transparency. Graphical reports provide complete visibility throughout the life of your project. It’s easy to understand why Relativity made a decision.
  • Flexibility. Assisted Review can be run for first-pass reviews or during more sophisticated issue coding. You can also run multiple Assisted Review projects in the same workspace and begin a new project at any point during review.
  • Ease of use. Assisted Review is fully integrated into Relativity, so reviewers don’t have to learn another software package or workflow.
  • Time and cost savings. By reducing the amount of data manually reviewed, you spend less time and money wading through volumes of electronically stored information.
  • Validation. Validation is built on statistical analysis, so you can be confident in your results.
  • Comprehensive text analytics. Beyond computer-assisted review, you can cluster documents, quickly find conceptually similar documents with a right-click, and do advanced analysis of keywords.
  • Real-world experience. Terabytes upon terabytes of data have passed through our analytics engine, while case studies and webinars have outlined Assisted Review’s use in the field.
  • We do more. Security, scalability, automated review workflows, processing, and productions are all part of Relativity. It is a complete system.
 

How can I use Assisted Review to improve my review process?

You can decide how to best use the process to fit your team’s review needs:

  • As a method of prioritization to get to the most important documents faster.
  • As a way to ignore large batches of non-responsive material.
  • As a QC tool to gauge the accuracy of a review.

How do I get started?

Assisted Review is fully integrated into Relativity as part of your applications library, so it’s easy to get a project up and running. It makes use of a Relativity Analytics index for training the system.

To see a demo of Assisted Review, please contact sales@kcura.com. For information on how to install the application or best practices for starting an Assisted Review project, please contact advice@kcura.com.

Click here to follow the Assisted Review story.

Click here to sign up for our monthly Assisted Review newsletter.

 

Assisted Review Webinars

 TitleSourceCategory
Ask the Doctor: David Grossman's Statistical Validation of Assisted ReviewkCura 
Computer-Assisted Review: As Seen from the FieldkCura 
The Statistics behind Relativity Assisted ReviewkCura 
Understanding and Implementing a Computer-Assisted Review WorkflowACEDS 

Assisted Review Press

 TitleSource
Predictive Coding from Theory to Practice - kCura's Relativity Assisted ReviewESG
The New Axiom of Computer-Assisted ReviewKMWorld
Review of Relativity Assisted ReviewLitigationWorld

Assisted Review White Papers

 TitleSource
Document Categorization Using Latent Semantic IndexingContent Analyst
Measuring and Validating the Effectiveness of Relativity Assisted ReviewkCura
Understanding the Components of Computer-Assisted Review and the
Workflow that Ties Them Together
kCura

Assisted Review Case Studies

 TitleSource
Millnet Relativity Assisted Review Case StudykCura
Complete Discovery Source Case StudykCura
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