The core ROSS legal research platform can now be used by researchers in every area of American law, as it now includes a full...
Meet Graham Toppin: Head of Engineering at ROSS Intelligence
Graham Toppin, ROSS Intelligence's new Head of Engineering shares a bit about his past and what made him embrace the future, jump into legal technology and join the team at ROSS.
I’ve decided to join the team at ROSS Intelligence this year. Coming from a background that has touched Telecommunications, Finance, Databases and horizontal technologies (like the Internet of Things, Big Data and Computational Linguistics), Legal Technology might seem to be a bit of a departure.
I’d like to share with you what I see at ROSS Intelligence, why it is a unique and fantastic opportunity, and why I decided to join Jimoh, Andrew and the team in redefining the Legal Industry.
When I’m evaluating a company to work at, I think about three things: the domain (i.e. what market and industry are they playing in), the technology (are they doing something interesting, new, exciting, proven, other?) and finally – and most importantly – the team (are these people that I can take the startup journey with).
LegalTech and Social Change
When I first heard about ROSS Intelligence, my first impression was that there wasn’t a clear connection between my talents and Legal Technology. The machine learning problems in Legal, as I understood them, were difficult, and not easily tractable.
However, ROSS persisted, and on a blustery fall morning late last year, I met with Jimoh Ovbiagele, ROSS’ CTO & Co-founder outside of Dineen Coffee in downtown Toronto. By coincidence, this spot was near to a small park where, in 1993, I had first come to Canada to study from Barbados. Back then I was greeted by Austin “Tom” Clarke, an old family friend who met me in that same park, and showed me around Toronto. In a fit of nostalgia, I asked Jimoh to join me on a bench in the park (now called Cloud Gardens), and we started talking about old Toronto. Our walk took us around downtown Toronto, through Bay Street, across the University of Toronto, to Kensington and up to Yorkville, sharing stories of the city and how it had changed in the last 30 years or so.
Change was a central theme to our discussion, and Jimoh shared with me his experiences with the legal system in the states, in particular his mother’s issues, and how technology could enable social change. I shared with him my views on growing flat, organic innovation centers, fusing applied research and engineering. We also bonded on our data-first approaches to machine intelligence – that is, get the data first, and the algorithms will evolve naturally as a consequence.
The Technology and the Team
Another requirement that I had was being able to answer my own needs and desires for my next career step. My two deep loves, professionally, are growing teams – and the members of those teams – and building amazing artificial intelligence technology. I needed to know that ROSS was up for the challenge of building a flat, collaborative, high performance environment.
Even more than that, I want to build something “specifically incredible” here at ROSS. The ways that we build software periodically undergo seismic shifts: We are constantly learning new ways of conceptualizing, building and deploying software. The advent of object-oriented programming was one, the emergence of supply chain management another. Mobile changed the way that we think about devices and how they integrate with our lives. These technologies made us as human beings better and more effective on the whole.
They also necessitated a different way of building. In 2007 when the iPhone was launched, and then in 2008 when the App Store became something significant, many companies had to scramble to understand how to integrate mobile into their products. They also had to rethink how they built their products.
With respect to AI, the last few years have seen statistical methods that were previously infeasible, become practical, efficient, and objectively superior ways of building software. At ROSS, I see an opportunity to integrate Machine Intelligence from the ground up into a team of high-performing engineers for whom Deep Learning is a natural synergistic part of how they build.
Jimoh and Andrew both have an intuitive, well-grounded view of this landscape, how they can compete, and how they can win. We were able to easily see how my vision of this team worked well with their larger ambitions.
I joined ROSS Intelligence at the start of this year, and it’s been a heady, intense first month. We’ve merged our Applied Research, Product and Engineering teams into a single entity – Delivery. We’ve created a unified roadmap, and started to build out the infrastructure necessary to drive value into our product earlier, more efficiently, and with a better user experience.
How will this affect you, our users? First, you’re going to see a faster, snappier, easier to use product. This week, we’re announcing EVA which shows our early strides in performance driven, customer-centric product. Second, you’re going to see our product get faster, easier to use, and cover more of the practice areas that you care about.
Our goal is to make Legal Research fun, engaging and cost-efficient. And to have a ton of fun doing it. We’re looking forward to taking that journey with you!
ROSS is an advanced legal research tool that harnesses the power of artificial intelligence to make the research process more efficient.
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