Predictive Coding, Technology Assisted Review

Streamlining the eDiscovery process with smart technology that works fast.

The biggest cost in eDiscovery are the legal fees paid to attorneys who review documents for production. Reducing the number of documents for review will have a serious affect on your bottom line.

DSi uses technology assisted review (TAR) to reduce the unnecessary review of thousands, sometimes millions, of non-responsive documents. TAR identifies important documents early in the review process and prioritizes them, so you don’t have to pay lawyers to do this.

We offer technology assisted review with all of our review platforms, including Catalyst, Ipro Eclipse and Allegro, and Everlaw and the use of predictive coding is a common occurrence.

We throw everything we have at large datasets to whittle them down to a manageable size. DSi’s suite of TAR procedures includes advanced filtering, keyword analytics, predictive ranking, predictive coding, automatic single-click redaction, powerful email threading, end-of-branch coding and TAR 2.0, which features continuous active learning.

Our sophisticated algorithms and advanced tools allow us to effectively reduce large data populations in a defensible manner, creating significant cost reductions as lawyers spend less time reviewing non-responsive documents.

Curious about predictive coding? Let us introduce TAR 2.0.

The next frontier in eDiscovery, continuous active learning (CAL) – what we call TAR 2.0 – finds relevant documents more quickly, with less effort and at a lower cost than TAR 1.0 platforms, and it has been proven to be the most effective predictive coding solution.

CAL is the only methodology with a machine-learning algorithm that continues to adapt as new documents are fed. With TAR 2.0, every coding call contributes to the discovery of “(more like this)” documents. This prioritization happens automatically within the system, ensuring that reviewers are only looking at the highly relevant documents first.

Benefits of TAR 2.0:

 

  • It works well with rolling data
  • Subject matter experts are are not always necessary
  • It can be run individually on multiple issues
  • Data population can be easily and quickly re-ranked based on new or additional search criteria
  • It more efficiently reduces costs
  • It’s flexible, fast and defensible

 


If you’re interested in learning more about how technology assisted review adds defensibility, consistency and quality to the review process, contact us or checking out these resources:

 

Overview of Technology Assisted Review (infographic)

Using Predictive Coding (case study)

TAR 2.0: The Next Frontier in eDiscovery (blog)

Is your TAR temperature 98.6? (case study)


Advanced Filtering

Advanced Filtering

Details

DSi engages powerful filtering, sophisticated analytics and search tools to simplify your eDiscovery review and reduce costs.

Predictive Coding, Technology Assisted Review

Predictive Coding, Technology Assisted Review

Details

DSi’s Technology Assisted Review (TAR) solutions help counsel make the best use of their time.

Eclipse Review

Eclipse Review

Details

Ipro Eclipse is a cost-effective review platform that handles large amounts of data and integrates seamlessly with Allegro to simplify the early case assessment process.

Catalyst Hosted Review

Catalyst Hosted Review

Details

Catalyst relies on continuous active learning, which we call TAR 2.0, to provide the world’s most powerful review solution.

Clearwell Review

Clearwell Review

Details

Clearwell is a litigation support option that covers the entire eDiscovery lifecycle and is particularly effective during early case assessment.

Everlaw Review

Everlaw Review

Details

Everlaw is a robust cloud-based review tool that integrates case outlining and evidence organization into the user-friendly platform.

The eDiscovery landscape changes fast, and your IT must change with it. Stay up to date with new technologies, big data, forensics and more.

Get Resources

What is your TAR temperatureIs your TAR temperature 98.6?

Download this free case study and find out!

 

Learn how we leveraged the TAR 2.0 platform to find the responsive documents out of an already filtered population of 2.1 million. Approximately 98% of the relevant documents were found after viewing only approximately 6% of the document population.

Check out the incredible benefits of TAR 2.0 with this free case study