Everlaw does great for e-discovery in mass tort cases
July 07, 2021

Everlaw does great for e-discovery in mass tort cases

Anthony Foster | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with Everlaw

Everlaw is used in my firm in mass tort cases. It helps us deal with the massive amounts of documents and files provided to us in the lengthy discovery process that mass tort cases have. Here, Everlaw helps organize these massive amounts of documents, lets us access them in a manageable way, search for documents that we need, and accomplish the document review that we need in our mass tort cases. It is a tough task, but Everlaw does make it better.
  • Organization
  • Flagging and keywords of important points in documents
  • Making document review easier
  • Organization
  • Connectability between different users within the firm and other firms on our team
  • Keyword tagging
  • Allows for attacking document review in mass tort cases
  • Helps get discovery process done sooner
  • Sooner finish of discovery means quicker to settlement or trial
I've used something called blade.acorn in a different mass tort case. I did not like it as much as Everlaw. Maybe it was because I used Everlaw first and was used to it. But Everlaw does have a great and organized platform that I think is better and is well-suited for mass tort cases' discovery process.

Do you think Everlaw delivers good value for the price?

Not sure

Are you happy with Everlaw's feature set?

Yes

Did Everlaw live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Everlaw go as expected?

I wasn't involved with the implementation phase

Would you buy Everlaw again?

Yes

Everlaw is great for organizing large quantities of documents and helping our entire team and other teams across the nation communicate and attack the huge document productions in an organized and efficient manner. It allows us to break apart the huge document productions and hit them piece by piece and apply tags and keywords to the documents.