Faster Insight, More Organized, Better Prepared.
Language-Based Analytics (LBA) is a language-based approach to reduce the volume of collected documents by identifying potentially relevant information in the early phases of eDiscovery. With Language-Based Analytics, organizations can quickly and cost-effectively analyze a document collection, understand each document, and make important strategic decisions based upon this understanding.
Reduce eDiscovery Costs with a Revolutionary Approach to Keyword Development and Filtering
Language-Based Analytics quickly identifies the review documents that matter. For attorneys who are truly experts in their field, LBA delivers results that no machine can match, without the uncertainty and opacity of complicated algorithms and with an unmatched savings in time and cost.
Most attorneys have experienced an informal version of the LBA approach when they create keyword filters, but the challenge with traditional keywords is identifying the right words that hone in on the relevant documents without dragging in a lot of extraneous ones. LBA solves this problem with a structured approach to keyword development that quickly provides attorneys with faster insight into the language used in the relevant files within the collected dataset. In short, it turns a fill-in-the-blank exercise into a multiple choice exercise – thereby ensuring better results and less risk.
Accelerate Review with our Highlight-Driven Bulk Tagger
Language-Based Analytics℠ Review Acceleration (Vestigate®) dramatically accelerates review and delivers substantial savings. Built into kCura’s Relativity® user interface, Vestigate’s patented highlight-driven bulk tagger allows reviewers to highlight language they deem responsive, issue code it, and with a click of the mouse, remove all documents from the data set with that same highlighted language.
Find out why Vestigate was a finalist for kCura’s first Relativity Fest Innovation Awards in the category of Best Service Provider Solution.
Choose Language-Based Analytics when you want to:
- Lower your costs dramatically without artificial intelligence.
- Gain faster insight into your collection and the language used in files relevant to the case.
- Reuse the work product on subsequent batches and across matters.
- Spend less time on administrative aspects and more time on strategic legal decisions.
- Avoid looking at multiple documents that contain the same relevant language.
- Complete 1st pass review before reading 20% of the text-based documents.
- Audit reviewers’ work in real time.
Language-Based Analytics for Incoming Productions: Quickly Pinpoint Key Documents and Gain the Necessary Insight to Formulate Important Case Strategies Very Early in the Process
Incoming productions are becoming an increasing burden due to accelerated dockets, increased volumes of data and clients’ reduced budgets. Oftentimes they are fraught with irrelevant documents, either due to overly broad keywords or the lack of a thorough review. This puts the onus on the receiving party to determine:
- Did the opposing party meet its production obligation?
- Did we request the right documents?
- What do the documents say about the issues?
- Which documents should we use as exhibits?
Language-Based Analytics for Incoming Productions delivers these answers with minimal effort by counsel.
Leveraging the language in the document request and the attorneys’ knowledge of the matter, Boolean queries are run across the production – allowing documents to be categorized and tagged by the issues in the case.
This simple step makes it easy to see whether the opposing party met its production obligation and whether the right documents were requested. It also arms you with valuable data you can use in your motions practice and pre-trial conferences, such as:
- How many documents were produced in response to each issue.
- How many completely irrelevant documents were produced.
You will be able to identify any deficiencies with specificity that will likely surprise the producing party.
Utilizing this methodology to categorize and prioritize your documents, you will dramatically save review time and money, and be 95% certain you have seen all of the relevant documents.
Language-Based Analytics for Incoming Productions reduces your costs while raising the bar on the speed and depth of understanding you can gain from an incoming production.