AI Legel Digita, Image by herbinisaac from PixabayEverlaw, the cloud-native litigation and investigation platform, has announced the addition of three new features to its AI suite. It also unveiled the latest update to its platform, Multi-Matter Models. Details of all the Everlaw AI capabilities are hidden in a horrible initial webpage interface that one must persevere through to get to the details.

Everlaw AI components now contain:

  • EverlawAI Assistant (new)
  • Predictive Coding (new)
  • Clustering
  • Advanced Analytics
  • Machine Translation

The EverlawAI Assistant

Top of the list is the EvelerlawAI Assistant, which combines generative AI with advanced analytics. Everlaw hopes to bring the solution to general availability later in 2024. However, the solution is ready for launch, having been in a closed beta program since July 2023. Currently, over 1,000 legal professionals in 40 customer firms are using the solution.

The solution includes Review Assistance and Writing Assistance. Review Assistance provides coding suggestions, document summaries, people and organization extraction, sentiment analysis, and custom document queries. It helps with the review of documents with near-instant insights and summaries.

The second element is Writing Assistance, which assists legal teams with the creation of a first draft when creating statements of facts or deposition summaries, with citations to supporting documents included.

One of those beta program users is Cole, Scott & Kissane. Manuel Delgado, Litigation Support Manager, Cole, Scott & Kissane, commented, “EverlawAI Assistant proved helpful in reaching a settlement. With it, we were able to quickly summarize dozens of financial reports prior to conference. Some of the insights we gained caught the plaintiff by surprise. A settlement was solidified thereafter, and our client was thrilled.

“I have found EverlawAI Assistant a useful tool to interrogate data in complex documents to quickly ascertain our position. For example, if I have a deposition — let’s say 300 pages long it could take hours to summarize, and the AI Assistant can do it in less than a few minutes with a topic index that we can then fact-check. In complex cases, such as employee, construction and insurance work, having a tool that will get my clients ahead of the game is invaluable for the firm.”

Two new features for Review Assistance

Everlaw has also added Coding Suggestions and Batch Summarization to the AI Assistant. This is an option that legal teams can have turned on if they wish. When active, it makes suggestions about whether a code with user-configured criteria should be applied or not. Users can see how Everlaw AI reached this decision to suggest the addition to help them determine whether to agree or not. Using this new feature, reviewers can determine whether the suggestions enhance their searches to help find material insights within documents faster.

AJ Shankar, Founder and CEO of Everlaw, image credit: LinkedIn
AJ Shankar, Founder and CEO of Everlaw

Batch summarisation enables users to create summaries of multiple documents quickly with a single click. The solution can analyse any number of documents from two up to the entire corpus within the eDiscovery workflow. The solution provides a table of document results for easy consumption alongside the summary. Overall, it makes it easier and faster to understand what lies within a corpus, enabling the legal team to understand the key matters faster.

AJ Shankar, Founder and CEO of Everlaw, commented, “With embedded GenAI, the Everlaw platform is helping legal teams navigate eDiscovery, build their case and speed their time to resolution,” said, “We’ve got 1,000 people on board and the exciting part is seeing how the early adopters have already gained advantages by outmanoeuvring their opposing counsel.”

Platform update with multi-matter models

This new AI-based feature allows legal teams to apply their previously trained predictive coding models to new cases. The feature presumes the ability to save models from existing cases for later re-use on different cases. This could be extremely useful for class actions, where legal teams need to sift through vast swathes of similar but not always the same piles of documents. It could also be useful for corporate lawyers facing similar cases.

The new models include the following capabilities:

  • Leverage one or more of their previously trained models on similar new matters to save time and jumpstart AI-powered review
  • Create a library of lasting, reusable models to capitalize on past work continually
  • Tailor that library to pinpoint the legal challenges their teams face regularly

Multi-matter models will be available in spring. Shankar commented, “No more starting from scratch every time you tackle a new case with Predictive Coding. Multi-Matter Models apply your previous work to future cases for faster time-to-value and allow you to build a portfolio of reusable AI models for your organization.”

Enterprise Times: What does this mean

Details of the solutions are light. Hopefully, Everlaw will create more videos to support the general availability, so firms can better understand the new capabilities. These new features extend the use of AI across the Everlaw platform and could bring a welcome boost to the productivity of firms during the review process. Hopefully, Everlaw will also improve the design of its AI-Analytics webpage.

DOI deploys Everlaw to answers FOIA requests faster and more accurately



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