Technology Assisted Review (TAR) & AI for eDiscovery & Investigations
Review data more precisely and efficiently than ever before.
Client data in all their forms continue to expand, making fact development in legal and internal document reviews incredibly daunting. Moreover, review costs have proven to be the largest component expense in discovery, creating a discovery landscape where matters scarcely reach the merits before litigation budgets are well exceeded.
vdiscovery tackles this problem with a layered approach that prominently features Technology Assisted Review and predictive coding. vdiscovery is an industry leader in deploying Artificial Intelligence and Machine Learning for the next generation of TAR for ediscovery, and for all manner of internal investigations and data analysis.
vdiscovery’s TAR services enable clients to:
Review millions of documents at lightening pace
Surpass limits of Boolean-based searches
Leverage machine learning
Surface relevant analytics in minutes
Create portable models for diverse investigations
Use visualization tools to expand discovery approach
Boost relevant data to the top of list quickly & effortlessly
Reduce overall costs of ediscovery
Increase case defensibility
Detect patterns and relationships among unfamiliar document sets clustered according to their topics on a visual, clickable wheel.
Detect critical communications, and avoid wholly repetitive review by seeing only the most inclusive threads in an email chain.
Use visual dashboard built in to the latest Relativity versions to learn relationships between your documents or even just their metadata. Clickable graphs and charts and visual search interface allow easily filtering and tagging.
Continuous Active Multi-Model Learning
Review with an AI that continuously adapts to your coding and rearranges your queue to show you documents most like what you are coding for. We can even run this process directly in Relativity!
Did you train a great model to detect a particular behaviour that interest to your company or firm? Leverage the useful model across any similar set of data, for any matter.
Perform TAR I predictive coding using rounds of review and statistical analysis of results.
Identify and remove substantively similar documents that did not meet the tight standards for "exact duplicates”. Create “% similar” field visible in Relativity.
Related Term Detection
Discover important terms and potential code words in a data set by entering relevant known terms into the analytic engine.
Find Similar Documents
Leverage known hot documents or examples of privileged communications to quickly locate others like them.
Finding relevant information quickly is key to efficient and timely action in your matters:
- Compliance & regulation
- Finncial control/audits
- Workplace harassment
- Employment discrimination
- Corporate governance
- Financial crimes
- Data security
- IP theft
Need a quote on a new project? Give us a bit of detail on your project and we'll get back to you! →