The $400 billion legal market has attracted little venture capital investment and remained arguably under-disrupted by technology. Even as other professions — notably financial advisers and marketing professionals — are being transformed by new technologies, tech companies haven’t found as many opportunities in the legal space, where many time-consuming tasks that demand human intelligence have defied automation.
That’s starting to change. Key advances in two technologies are hatching a new Legal Tech market. They are:
MACHINE LEARNING: ML is a form of artificial intelligence that uses algorithms that recognize patterns and adapt in order to create increasingly accurate predictions. Consumers experience basic models of ML when Netflix recommends movies to subscribers, or Pandora selects songs, and it is also at the heart of using sensor data to control self-driving cars.
NATURAL LANGUAGE PROCESSING: NLP systems, another form of artificial intelligence, can understand and use a spoken or written language such as English, rather than a specialized computer language such as C++.
NLP and ML together can understand documents like a human, but with high-speed computational power and vast digital memory. This has been used for years in applications like the iPhone’s Siri and IBM’s Watson.
But now, startups can quickly and cheaply deploy these tools. AWS and other cloud computing platforms have made computational power cheap and ubiquitous. NLP libraries have improved to the point that non-NLP developers can use them.
Already we’re seeing interesting applications from early stage startups, including automated personal assistants (JulieDesk, X.AI), finance tools (Social Alpha, AlphaSense), marketing (Macromeasures, EncoreAlert) and language generation (Easyop).
It’s the big law firms, however, that are poised to be irreversibly changed as startups enter its field:
Text IQ: Using NLP, ML, and social network mapping, Text IQ helps determine privilege in eDiscovery. For example, if a text message between two employees says, “Joe said we can do it, if we get approval”. That text is privileged and does not need to be turned over to opposing counsel if “Joe” is determined to be that specific Joe from the general counsel’s office.
RossIntelligence: Built on IBM’s hefty Watson platform, Ross does deep legal research. Instead of a team of associates looking through a curated list of precedents, Ross could, in theory, look at all cases related to a particular law and pull out the most relevant passages for their review. Further, ROSS notifies lawyers of new court decisions that can affect their cases.
Counselytics: This service determines how above/below market a lease agreement is, or how closely a contract compares to historical deals. For instance, it might report, “The lease is out of market as these X terms are greater than 90% of all contracts in the database.”
LitIQ: This program highlights ambiguities within contracts or other legal documents to prevent drafting errors and disagreements. For example, if a contract says “X and Y or Z,” LitIQ asks if the user meant (X and Y) or Z or X and (Y or Z). The company’s goal is to be able to determine if there are logic conflicts between paragraphs within a legal document.
eBrevia: Using technology developed at Columbia University, their software extracts and summarizes key provisions from legal documents. The main uses of the software are for due diligence, contract management, lease abstraction, and document drafting.
Surveying this field, two things stand out. First, even though they all rely on the same core technology and target the same market, there is little to no overlap. Second, most of these companies are targeting the work currently done by high-paid associates at big law firms. Will the upshot be that associates do less mind-numbing work, or that law firms will need significantly fewer associates?
So what does this all mean?
These early stage startups have not yet proved the tech can live up to its potential, but none has flamed out, either.
If these show success, expect more startups to enter the legal space and more focused attention from venture capital to seed them.
Most of these startups must sell to the major law firms, and as a result, those big firms have the power to dramatically retard their growth speed. But if a few firms find the technology provides competitive advantage, the whole market quickly will follow suit (if only to protect themselves against malpractice claims).
My theory is that Big Law is about to change. Firms that are proactive in implementing new technology have an opportunity to increase productivity and market share. Those that resist will face significant pain in five to 10 years, when they will be playing catch-up.
TLDR: A fusion of two technologies—natural language processing and machine learning—mean computers can understand written documents and analyze them for patterns and inconsistencies. This holds tremendous promise for a burgeoning Legal Tech sector, where a bunch of startups are automating work traditionally done by armies of high-paid associate lawyers.