Technology-Assisted Review
Find the most relevant documents with two powerful technology-assisted review workflows: active learning and sample-based learning. Choose the workflow that works for you, or use a combination of both.
The Speed of Active Learning
RelativityOne’s active learning workflow leverages machine learning to continuously assess what’s important and serve up relevant information faster.
Accelerate insights
Code documents, and active learning will automatically surface the most relevant ones next.
Leverage real-time intelligence
Every coding decision makes active learning smarter. No extra input needed.
Get started with minimal setup
Stand up your project right away – and without a single training set.
Jump-Start Your Review with Sample-Based Learning
Let RelativityOne do the heavy lifting, while you focus on reviewing only what’s relevant.
Save time & money
Give RelativityOne a seed set of documents, and it will suggest coding decisions for you. Work with it to refine its understanding and save on your review.
Review smarter
Send documents that are coded responsive to your most qualified experts. Pass the uncategorized ones to other reviewers for QC.
Trust a proven & accepted workflow
RelativityOne’s sample-based learning workflow has been proven effective by hundreds of organizations and approved by courts across the globe.
“Analytics is on the rise throughout Australia as there is more litigation and regulatory action. Active learning in Relativity has helped us seamlessly handle these complex reviews – and get the job done quickly.”
Craig Macaulay, Executive Director, Forensic Technology
Assisted Review is all part of RelativityOne. Ready to learn more?
Learn more about Assisted Review in RelativityOne
Relativity’s Approach to Active Learning and the Tech Behind It
Learn about the tech that drives Relativity’s active learning workflow and how to use it to monitor and validate your projects.
icourts Saved $5 Million with the Power of Active Learning
Learn how icourts integrated active learning into their workflow to save 28,000 hours of review time.