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BGV Perspectives: The Legal Tech Market

Yash Hemaraj (Principal at BGV) and AJ Singh (BGV Intern and MBA candidate from Duke University) share their perspective on Legal Tech market.

Following the eDiscovery boom of the late 2000s, startups began developing technology innovations to address other facets of legal spend for large corporations swimming in litigation bills. Couple these propositions with the buzz phrases “machine learning” and “artificial intelligence” and venture capital investment has climbed sharply in this space since 2012. While legal tech investment totaled only $155M in 2016 relative to $289M in 2015, 2015 funding represented a 250% increase over $114M in 2014. Thus, 2016 warranted a return to normalcy.   Despite the massive size of the Legal Industry ($300B), Venture Capital investment in the legal tech sector has been modest.

Deal flow in 2016 increased 12% to 67 versus 60 in the prior year, according to CB Insights. Furthermore, Q4 2016 saw 27 deals completed, the highest quarterly amount yet in legal tech investment.

 

Legal Research

Innovation within the legal research domain has seen great advancements and subsequently significant dollars invested. Investments are primarily made in either case law research or litigation analytics. Data acquisition costs vary and may be prohibitive depending on the segments a start up chooses to disrupt.

 

Case Law Research

Natural language processing (NLP) technology has helped to shorten the case law research process for litigators looking to find relevant cases based on a chosen litigation strategy.

All legal research data relies on a central government repository – the Public Access to Court Electronic Records (PACER). PACER provides access to judicial opinions – the judge’s ruling and her reasoning – free of charge. Startups in this field allow users to directly query these opinions through a proprietary platform, where the software ‘learns’ the intent behind users’ queries to narrow down results to the most relevant cases. Traditional Boolean and Natural Language searches from major legal research platforms are far broader.

With no data acquisition costs, firms face low barriers to entry and thus the case law research space is teeming with competition. Interviews with practicing litigators highlight that most offerings are substitutes for one another with the promised game-changing technology falling short of its hype. Furthermore, big firms have not yet fully bought into overhauling their research processes. Jeff Ward, Associate Clinical Professor of Law at Duke University’s School of Law and Director of the Duke Center on Law & Technology, explains:

“We are in the nascent stage of AI and machine learning adoption in legal tech. There is still hesitation in the industry; the visionary firms who are testing these research advancements typically do so with associates running these platforms in parallel to their traditional research methods.”

Amidst this crowded space, firms with the most traction include ROSS Intelligence, CaseText, and Judicata. As competitors are still unable to present a robust product differentiation strategy, we believe significant opportunities exist to develop a truly impactful technology not only in the US but also in major international litigation domains.

 

Litigation Analytics

While case law research relies on uncovering relevant cases to bolster a litigator’s position, litigation analytics provides “predictive” likelihoods of success given a certain strategy against a chosen judge. Furthermore, this space is growing subsequent predictive verticals such as “litigator analytics” to predict the lawyer’s likelihood to win a case and “jury analytics” to predict the odds of success given the jury’s composition.

 

 

Litigation analytics uses data from court dockets, which describe the procedural evolution of a case, also through the PACER website. Unlike case law research, court dockets cost $0.10 per page with a $3 cap per docket. Thus, the cost to compile a meaningful set of dockets in each jurisdiction is exorbitantly high.

Couple this with big players such as Bloomberg Law and Lexis Nexis (by way of the Lex Machina and Ravel Law acquisitions) providing litigation analytics services, startups in this sphere must have the most complete set of court dockets in order to have a fighting chance against big name incumbents. The high data acquisition costs coupled with larger, trusted players already in the space lead us to believe that litigation analytics is an unattractive sphere of legal tech investment.

 

Contract Management

Innovation within contract management centers around saving firms time and money by shortening contract review cycles. Through NLP and artificial intelligence, software providers such as Luminance cut down due diligence times by filtering out contract irregularities. Furthermore, the software uses clients’ prior documents to build on the ability to screen for questionable clauses.

The use cases of this technology are widespread: law firms can add this technology to further refine their existing contract review offering, while corporations can utilize the NLP algorithm during internal audits, regulatory reviews, and M&A due diligence. We believe there is great promise for the contract due diligence use case in this subset, but the compliance use case requires further NLP capabilities (more on the compliance use case below).

 

eDiscovery 

eDiscovery is the process of compiling electronic data during the discovery period of litigation and distilling it down to the most relevant documents. The practice took off in 2006 and is now a maturing industry with thinning margins. Service providers are offering an increasingly homogenous product and major software providers are dropping channel partners to go straight to market – both of which further reduce margins.

Most legal tech advancement in this space involves add-on machine learning software such as Brainspace’s unstructured data analysis product that synthesizes and clusters documents based on conceptual similarity. Other intriguing platforms include Veritone Law, which uses NLP to digitize and parse audio/video on top of kCura’s prominent eDiscovery data processing and hosting platform. We believe this audio/video technology, when coupled with contract management NLP software, provides a powerful tool for compliance departments. Ciaran Power, President and co-founder of eDiscovery service provider Discovia (acquired by Lighthouse eDiscovery), notes:

“Compliance spend is much bigger than eDiscovery. A dream and quickly becoming a reality are compliance departments that can in real time listen to employee calls and quickly be alerted to compliance concerns. There is tremendous value to a bank to be able to quickly realize that an employee is talking on the phone in code about insider trading.”

 

Legal Tech Going Forward

In summary, we believe the case law legal research vertical holds the greatest upside for venture capital investment. Furthermore, we think a natural extension of the case law platform to be a contract management suite that either specializes in contract due diligence or incorporates audio/video NLP technology for compliance use cases, or both.   Professor Ward states:

“Early movers in case law tech are working to refine their NLP capabilities. Once a firm can deliver high-powered technology and couple this with a full suite of legal tech parsing software such as contract analysis, they will be able to make the case for a truly powerful supplement to the legal toolkit.”

 

We would love to hear from you, get in touch with us to share your thoughts and comments.

  • 20 Oct, 2017
  • Posted by Anik Bose
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