AJ Shankar was busy working on his PhD thesis at the University of California, Berkeley in the prestigious Programming Systems Lab, where he published a number of important papers in OOPSLA and PLDI. As a big fan of side projects, he also caught the maker bug.
One of those projects was working as a technical expert for a leading Seattle-based law firm. It led AJ to ask what every entrepreneur asks, “How can this be improved with software?” That’s where Everlaw got started, in 2011.
The legal profession — particularly the area of litigation and trials — is a costly, complex, labor-intensive, and, frankly, error-prone process. Beyond that, it is steeped in the complexities of individual courts and jurisdictions dictating, sometimes at the trial level, how technology can be used. Having personally worked through the transition from WordPerfect to Windows over the better part of a decade, I know the challenges of bringing technology to this highly knowledge- and people-intensive process are significant.
AJ and his co-founder, practicing lawyer Jeff Friedman, a former Assistant U.S. Attorney and corporate counsel, know these challenges well from their experiences. They set out to invent something that meets both the demanding technical needs of litigation along with the unique business requirements of law firms, which often do not have the resources or skills required to manage complex software deployments.
In fact, complex deployments of on-premises software defines the current state-of-the-art in litigation support software. Anyone familiar with modern software would look at this “state-of-the-art” and see architecture from another era. That’s not to say those solutions do not provide value and make money, but AJ and Jeff see a far better way.
There is also a need for modern solutions to deeply technical problems — such as searching terabyte corpora for relevant documents (the state-of-the-art is mostly keyword search) or identifying clusters of relevant documents based on machine learning techniques (versus relying on humans to manually sift through and connect millions of documents). Historically, an industry vertical with such a legacy business model and architecture (i.e., very slow to change) would have a very hard time attracting top computer science talent to improve the space.
Law firms also need software to solve the modern problem of “big data.” In this context, big data can mean millions of email messages, chat transcripts, voice mail recordings, scanned documents, entire data sets and social media feeds, and much more. Those are the artifacts of the legal discovery process that flow across both sides of the aisle in ever-increasing volumes. These volumes are beyond what many law firms can deal with, and as some might know, producing large amounts of data can often be part of a legal strategy used against smaller firms.
Finally, the pace of change for software in the litigation industry needs to increase. The model of one-time, slowly updated on-premises software simply isn’t compatible with the fast-paced changes in technologies that can help legal. Part of the legacy world the legal profession faces is the same that any enterprise faces: A desire to move away from high, up-front product costs and transition to a cloud and software-as-a-service (SaaS) model.
Everlaw architected a solution that starts from customers: attorneys at small firms, large firms, state offices, and on both the defense and plaintiff side of cases. AJ’s technical background and Jeff’s real-world experience as an attorney proved to be a great place to start. To begin the journey, Everlaw assembled an engineering team of hard-core computer scientists, many from UC Berkeley.
In the Andreessen Horowitz pitch meeting, it turns out a lot of the former CEOs, execs, and founders have been involved in litigation. Our collective experience, especially as defendants, led to an immediate bond with AJ as he detailed the Everlaw solution. Many of us have been through the boxes of documents and questions from counsel about “discovered” documents. We knew how difficult the process was and we loved when AJ detailed Everlaw’s approach:
1. Bring together core computer science experts from natural language, machine learning, and full-stack development to architect the system.
2. Build innovative experiences that start with the process of ediscovery and provide a platform for an end-to-end solution for attorneys to collaborate as a case is developed.
3. Deliver Everlaw as an incredibly secure, highly reliable, totally scaleable cloud-based SaaS service.
So far, their experience with customers has been amazing. Since most attorneys are part of the world of mobile and cloud experiences, as soon as they see Everlaw, they see how much easier, faster, and higher quality their trial preparation and work can be. In fact, customers usually say “why did it take so long” or “this is how it should work”. AJ has written a post that includes more details on the company’s vision and the success to date.
At Andreessen Horowitz, we are always incredibly excited to see technology founders taking on the hard work of reimagining an industry. It is clear that mobile, machine learning, and cloud delivered via SaaS will revolutionize every vertical, including legal. We love the work that AJ, Jeff and the Everlaw team have done to bring such high-powered efforts to an incredibly important part of the economy.
For those reasons, we could not be more excited to be partnering with Everlaw and leading their Series A funding round, joining the existing investors. I am super excited to be joining the Everlaw board to support their ongoing work. Software eats legal.