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 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)
• Is your TAR temperature 98.6? (case study)