Webcast

How to Leverage Predictive Coding and Artificial Intelligence for Defensible and Effective Review

Overview

On-demand Webcast

Sponsored by:

 

 

 

Do looming deadlines and a huge document corpus make review seem daunting? Curious about predictive coding but not sure how to set up a model? Learn how to leverage predictive coding and artificial intelligence to make the review process more efficient and accurate.

In this webcast, experts Kevin Kraft and Jennifer Roberts will address common questions and concerns related to predictive coding; while going through common use cases to demonstrate how to set up predictive coding models, and how to leverage predictive coding data throughout the review process. Attendees will also learn how to:

  • Use predictive coding to improve accuracy and control costs in the review process.
  • Pinpoint relevant documents for plaintiff side review.
  • Leverage multiple predictive coding models for a more comprehensive review, and a higher recall on the defense side.
  • Leverage predictive input for quality control to pinpoint areas of uncertainty and review human work for accuracy.

REGISTER NOW! (Not able to attend? STILL REGISTER you will receive an email with how to access the recording of the event)

Speakers:

Kevin Kraft | Customer Success Manager | Everlaw

Kevin Kraft is a Customer Success Manager at Everlaw and is licensed to practice law in California. In his role, he builds and nurtures relationships with Everlaw customers to ensure their successful use of the platform. Prior to joining Everlaw, Kevin worked as a litigation associate and has extensive knowledge of the ediscovery process in litigation.

Jennifer Roberts | Product Marketing Manager | Everlaw

Jennifer Roberts is a Product Marketing Manager at Everlaw. She is a graduate of the Yale Law School and is licensed to practice law in California. Before joining Everlaw, Jennifer worked for several other companies in the legal industry and also worked abroad for clients in Europe, Asia, North, and South America.

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