On one hand, the volume of electronically stored information is too great to thoroughly review with limited resources. On the other hand, the risk of leaking sensitive documents is unacceptable. Attorneys are left with two bad options.
or reduce time and cost.
Find privileged and responsive information that humans and search terms miss. Find reputation damage before it scars your enterprise.
Save tens of millions of dollars per year by automating the most expensive part of discovery.
Meet deadlines that are humanly impossible. Text IQ for Legal is 10x faster, on average, than the status quo.
Text IQ's Artificial Intelligence and Machine Learning is used by leading enterprises, in-house counsel, and outside counsel for a number of key use cases detailed below
Confidently automate and secure the document review process by eliminating false positives and false negatives during ediscovery to find privileged, responsive, and reputation-damaging information. Text IQ understands the nuanced ways sensitive communication can be considered privileged. Our AI discerns the context, relationships, and hidden meanings within unstructured data to accurately detect when legal advice is given. In the process, a comprehensive privilege log is automatically populated with natural-language reasons and scores.
Automatically identify and redact sensitive information like personal information (PI), protected health information (PHI), confidential, and privileged data from documents. Text IQ’s redaction software goes beyond just regular expressions and search terms, applying AI to accurately discover special category data (e.g. religious beliefs) and incomplete, incorrect, or hidden names and meanings that would otherwise be missed.
Surface unknown attorneys, domains, and law firms, and identify the true roles of those conveying legal advice across your organization.
Confidently and rapidly produce a population of Non Privileged documents, after a defensible Quality Control process.
Automatically assimilate human feedback on a small subset of documents to improve privilege scoring on the entire dataset.
Scores rank Potentially Privileged documents for a prioritized human review. Reasons, provided in natural sentences, form the basis for the Privilege Log.