Derrick Harris of GigaOM recently wrote, “The legal profession is inherently conservative when it comes to adopting new technologies and practices, but firms and lawyers that want to stand out in an evolving field might want to jump on the big data bandwagon sooner rather than later. Law firms took a beating during the peak of the recession a few years ago — large firms, especially, laid off staff and scaled back significantly on hiring — and many argue the profession will never be the same. Clients worried about their own finances aren’t as keen on forking over huge hourly fees as teams of associates and partners work their cases. The business model of law is evolving pretty rapidly, from flat-rate fee structures and on-demand legal advice to the democratization of certain services via companies like LegalZoom.” Read more
Posts Tagged ‘PureDiscovery’
Derrick Harris of GigaOM reports that PureDiscovery, a company we have covered in the past, has raised $10 million in Series C funding to reinvent enterprise search. Harris writes, “Rather than indexing documents and letting users perform keyword searches, PureDiscovery is focused on semantic technology and learning the concepts contained within a company’s content. We first covered PureDiscovery in early 2012, when the company was just beginning its push out of the legal field where it has already made a name for itself. The company’s software has proven effective in e-discovery, where it’s used to learn what’s contained within thousands of pages of documents turned over during litigation. PureDiscovery also powers patent search for LexisNexis, where it has analyzed hundreds of millions of patent documents and journal articles to surface the most-relevant content regardless of keyword relevancy.” Read more
Derrick Harris reports that PureDiscovery, a Big Data startup that we have covered before, thinks that it “has the answer to outdated enterprise search technology, and it’s called BrainSpace. The company claims BrainSpace can learn just about everything about how pieces of content are related to one another. That means users will become less dependent on searching for information because the platform will feed them what they want to know as they interact with other content.” Read more
Last month Magistrate Judge Andrew Peck, of the U.S. District Court for the Southern District of New York, issued an opinion in a gender discrimination case that had this to say about computer-assisted review: “Computer-assisted review is an available tool and should be seriously considered for use in large-data-volume cases where it may save the producing party (or both parties) significant amounts of legal fees in document review.”
In doing so, he just also may have made a case for the legal profession to do some more investigation of semantic technology in order to cope with its own Big Data challenges. In the mid-2000s, the Federal Rules of Civil Procedure were amended to take into account electronic discovery, so that both sides in a legal challenge would have to confer within sixty days of filing to disclose how they handled digital data. The beauty of the American legal system is that it requires each party to pony up information that is meaningful and responsive to the facts of the case. The dark side is that the proliferation of data inside businesses means employees are creating more and more data in lots of different ways, which means legal staff has to spend a lot more time sifting through digital realms of structured and unstructured information to discover what may have to do with a lawsuit or government investigation, what is responsive to the other party’s document request, and what is privileged information, too.
“It’s created a cottage industry in temp staffing – now there are temp lawyers, contract attorneys who work from $30 to $75 an hour,” says Jay Leib, Chief Strategy Officer at kCura, which makes the Relativity Assisted Review e-discovery text analytics software based on latent semantic indexing technology. “Just like we outsource factory workers, there are outsourced attorneys overseas doing document review to combat the amount of data that’s sprung up.” There is so much data out there that it’s entirely possible that a $3 million lawsuit could cost $6 million to litigate, he says.
PureDiscovery has announced “that it is combining the power of its semantic discovery technology with LexisNexis® LAW PreDiscovery™, the premier solution for electronic discovery processing and imaging. The integration between the two products will help litigation discovery professionals find the most relevant documents faster than ever before by integrating PureDiscovery’s LegalSuite product with LAW PreDiscovery. PureDiscovery’s semantic technology utilizes the company’s innovations in machine learning to produce highly relevant semantic matches.” Read more
PureDiscovery has announced a new version of PureDiscovery Legal Suite which includes ‘Focus,’ a semantic search visualization tool. According to the article, “The release includes significant changes to the products workflow through a more intuitive user interface and the addition of several compelling product features suggested by the rapidly growing PureDiscovery user community. The most frequently suggested and significant upgrade to PDLS is the addition of a visual search capability the company calls ‘Focus’.” Read more
Did you know that more U.S. patents were granted last year than for any previous year in the past forty-odd years, with the exception of 2006? So reports Dr. Mark J. Perry, professor of economics and finance in the School of Management at the Flint campus of the University of Michigan, here. That added a heap of patents – near to some 200,000 – to an already full plate that organizations often have to dig into, whether to identify patent infringers, to sell off some IP, to improve their existing portfolios with additional IP from other sources, or even to explore whether one of their own innovations is worth patenting.
Just as those patent grants surged in 2009, TextWise introduced as part of its semantic similarity matching API a service to help businesses expedite U.S. patent searching. That semantic search capability now is included as part of Innography’s IP business intelligence system for managing, protecting and getting ROI out of patents.
The semantic service Innography has partnered up with aims at helping the general population of business users – not just high-priced expert patent searchers – get “more like this” matches to generate good results without having to run iterative searches, Textwise president Connie Kenneally explains.