E-discovery providers are primed to make the shift from providing products designed for e-discovery to providing products for much more complex document analytics.


Casepoint is typically thought of as an e-discovery company, although it describes itself as a “leader in cloud-based legal technology solutions.” It recently announced a new iteration to its built-in AI and advanced analytics technology, called CaseAssist.

According to the Casepoint press release, the enhanced technology will “give users more insight and control over the analytics process with enhanced visualization capabilities and configuration templates.” Says Casepoint, the enhancements will provide a continuing learning AI platform for the review of documents. It will work with or without sample documents for eDiscovery, investigations, and other document-intensive review projects. It embraces active and ongoing machine learning. According to Casepoint, CaseAssist includes workflows with natural language interactions. It will enable users to find critical documents by quickly answering simple questions. And there are numerous other enhancements. See the website and Bob Ambrogi’s article for a more comprehensive description.


But to me, that’s not the real story. When  Vishal Rajpara, cofounder and chief technology officer of Casepoint,showed me the product, I noticed something called Data Story Builder. Rajpara explained that this allowed a user to prepare a “story” about such things as the pleadings, the case itself, or the defenses. The user can then ask CaseAssist to find documents that support (or are potentially antithetical to the story).


The CaseAssist tool thus provides really a different and much broader use case entirely than just e-discovery. And it transitions Casepoint from just an e-discovery provider to something more remarkable. Casepoint and companies offering similar products (see below) have in fact become data analytics providers. Analytics that can be applied to vast sets of documents not only to find what may be responsive to a discovery request but to frame the entire case or matter.


Rajpara seems to realize this. As he notes in the press release: “at Casepoint, we do not see AI as ‘nice to have – rather, it’s a core part of our technology, Increasingly, both law firms and legal departments recognize [the advantages} across a broad range of activities, including case strategy, early case assessment, litigate-or-settle decisions, and much more. {Emphasis added}


Here’s how CaseAssist could work in real life. Let’s assume I have a . client that’s just been sued in a multi-million business dispute. I get the call. As a litigator, I know the first thing I need to do is understand the case and develop a long term vision and strategy for the case. And identify the best end result. The sooner I do this, the better the outcome.


So one of the first tasks is to get my arms around the relevant documents that, right now, only my client has. But the in-house counsel is busy and really doesn’t have the time needed to find these documents. If CaseAssist does what Rajpara says it will do, my client can tell it what the case is about and it can quickly do a first pass at the relevant documents. Then I use the tool to review further and find other critical documents.


From this, I now have a subset of documents. Together with the facts I develop from my client, this subset can be used to create my story of what happened, my vision, and my strategy. Then I can ask the CaseAssist AI platform to find more documents to support or (perhaps not support) my theories.


Later, I can use the tool to find the documents I need to file a motion to dismiss or a summary judgment motion. And oh yeah, I need an expert to offer opinions to support my theories. What documents to give her??? Again, CaseAssist could provide a quick and seamless first pass.


By the way, with each task, according to Rajpara, CaseAssist learns. It gets better at finding the documents that support what I have postulated to it.


And notice I haven’t even gotten to discovery issues, which is what Casepoint’s original products were designed to deal with.


So we have moved far beyond an e-discovery tool now. We are now really talking about sophisticated analytical programs. Programs that can be applied to documents for all sorts of purposes that may have very little to do with e-discovery.


E-discovery providers like Casepoint and other companies in the litigation and document review field (see my recent post) are in a prime place to make this shift. A shift to providing products designed not just for e-discovery but for more complex document analytics. When you think about it, this is precisely what they have been providing for some time. But now they much more sophisticated tools with which to do it.


The new Casepoint CaseAssist is exciting not because of what it can do but because it’s a paradigm shift to a much broader field.