Exterro Proudly Presents
Artificial Intelligence (AI) Driven E-Discovery
Exterro was founded with the simple vision that applying the concepts of process optimization and data science to the way companies respond to litigation would drive more successful outcomes at a lower cost. Remaining true to our vision, we are proud to announce Exterro AI. Leveraging the latest innovations in Deep Learning, Exterro is infusing AI across the entire E-Discovery process, saving you time, money and getting you to the facts of the case as quickly as possible
Watch AI Live Demo WebcastExterro AI
Deep Learning Based AI
Exterro’s artificial intelligence capabilities are built on top of the latest innovations in Deep Learning, Natural Language Processing, compute intensive hardware processing and other related architecture approaches
AI across the entire E-Discovery Process
Exterro's vision is to infuse AI across every stage of the e-discovery process, saving you time and money in every stage
AI Smart Labeling Review
Exterro Smart Labeling leverages the latest deep learning technology innovations to help guide reviewers by constantly analyzing and understanding the context of their labeling decisions, and suggesting/queueing and labelling the most relevant unreviewed documents, saving significant time and cost
At NightOwl Discovery, we are consistently looking at advanced technologies to help our clients meet their discovery, compliance, investigations and data analytics objectives. The use of the Deep Learning AI technology like that seen in Exterro’ s Smart Labeling is a great way for us to optimize the document review process for our clients.
NightOwl Discovery
We're just getting started
Exterro Smart Labeling is the first instantiation of Exterro’s Artificial Intelligence(AI) vision to infuse AI throughout the entire E-Discovery process. In contrast with other vendors, Exterro’s use of AI is not limited to the Review phase of E-Discovery. In the very near future, we will be launching new AI capabilities that will drive efficiency in the identification, preservation and collection stages of the EDRM.
