SEQUIM, WA, 98382-8461
Intraspexion was founded on the idea that prevention was the best way to deal with the enormous cost of litigation. The cost is on the order of $350,000 to $400,000 per case, even if a company wins in court. So the only way to win is not to play. Before Intraspexion, no one had taken on that challenge. With Deep Learning we experimented, built a team, and put the enterprise-grade software together.
For customer confidentiality reasons, we can only talk about our test case. We realized how to build the training set of documents for employment discrimination and then automated the extraction process. We worked with two Deep Learning companies, MetaMind (acquired by Salesforce) and Indico Data Systems (a startup in Boston). Both reported that, when we used their pre-trained algorithm, the system reported that 99.5% of the emails were unrelated to the risk, but gave us an early warning as to about 20 emails. Within minutes, we could see that the system found one (1) pre-litigation employment discrimination threat out of about 5,000 emails in the subset of Ken Lay's Enron emails. Our system finds needles in the haystack.
Events scheduled for 2017:
On June 6, in Chicago, IL at the Association of Corporate Counsel's Legal Ops Conference, Intraspexion will be in the Shark Tank event at 11 a.m., along with Kim Technologies, Lex Machina, and Neota Logic.
On June 8, in Palo Alto, CA, Nick Brestoff (Intraspexion's founder and CEO) will give an invited one-hour talk in two parts. In Part 1, Nick will talk about How to Use PACER to Build a Litigation Risk Profile. In Part 2, Nick will describe what Intraspexion does and show screenshots of the screens that users see when they receive an early warning alert.