As generative AI transforms the legal profession, few companies have captured the industry’s imagination like Harvey, an AI platform built to automate complex legal and professional services work.
Backed by OpenAI’s Startup Fund and trusted by more than 500 clients in over 50 markets, Harvey is now expanding its global footprint — and has chosen Toronto as the site of its first engineering hub outside the United States.
To understand why Canada is playing a pivotal role in Harvey’s next chapter, Techtalent.ca spoke with Siva Gurumurthy, the company’s Chief Technology Officer.
Gurumurthy discussed the unique strengths of Canada’s legal tech ecosystem, how Toronto engineers will shape Harvey’s global roadmap, and the company’s vision for secure, customizable AI tools that meet the stringent demands of modern legal teams.
Why did Harvey choose Canada as a key market for its global expansion, and what unique opportunities do you see in the Canadian legal tech landscape?
SG: Canada has 35,000 law firms (including several existing Harvey customers), a robust list of exceptional companies who could benefit from using Harvey in-house, and a really strong talent pool. The combination of those three factors was critical in informing our decision to open in Toronto. We’ve had great early signals on technical talent in the Canadian market, so we are very optimistic about what we can build here. It’s the first office opening outside the US where we are hiring engineering talent, which I think is a strong indication of both our commitment to the market and how critical it is to our global growth strategy.
What role will the new Toronto office play in shaping Harvey’s global roadmap, and how do you see Canadian teams influencing product development?
SG: Our Toronto based team will play a critical role in accelerating our product roadmap. Specifically, this team will work on a few key areas of our product to accelerate how we support in-house legal teams and also how we enable customers to more readily customize AI use cases to their unique business needs.
Can you share your approach to hiring locally, and what types of talent and expertise are you prioritizing in Toronto?
SG: We hired Gary Lam as our site lead for Toronto. He has great experience including Netflix and Twitter, and is from Toronto so he’s thrilled to build out the team there. We picked Toronto because it’s home to great engineering talent, strong academic institutions, and a promising market for Harvey. We are hiring a founding team as we speak and plan to hire ~20 people across engineering and go to market by early next year.
How does Harvey’s AI platform differentiate itself from other legal tech solutions, and what makes it particularly suited for Canadian law firms?
SG: Harvey’s biggest differentiators include our commitment to security so enterprises who want to leverage AI but do so responsibly can do so with assurance it’s been a critical differentiator from us from the start. The second thing is customization–our Workflow Builder product allows firms to customize their own ways of working within Harvey at scale. Third is just our pace–if you look at our Product Brief this month the team built a brand new interface, a Word Add-In, dozens of global data sources, and an Outlook integration preview. Harvey’s pace of innovation and scale combined with our relationships with top model providers is a core reason we think Canadian enterprises will partner with us. Fourth is our relentless focus on AI quality, featuring domain specific outputs fit for legal and professional services.
Could you explain how Harvey leverages large language models (LLMs) to automate complex legal tasks while maintaining security and compliance?
SG: Absolutely–the best way to think about it is that Harvey customers get access to the best models fit for each specific purpose in legal and professional services, and we even publish which model is currently best for which output they are most interested in. But in addition, customers get to set up data retention policies that match their organization’s approach, no data is ever used to train the models, and the document upload feature can be customized to match your organization’s security and data retention policies. So you get the very best outputs with a premium focus on security and privacy and protecting customer data.
How does Harvey plan to address the specific needs and regulatory requirements of Canadian legal professionals?
SG: The short answer is thoughtfully–we have a Head of Privacy whose team’s sole job is regulatory compliance and partnering with our engineering and security teams to ensure we manage any updates to the regulatory environment given how quickly they evolve. Anita Gorney, our VP of Privacy, is coming to Toronto for a speaking engagement this month and meeting with our customers while doing so, so I look forward to her updates after that visit.
Looking ahead, what is Harvey’s long-term vision for innovation in legal AI, and how does Canada fit into that journey?
SG: The long term vision for Harvey is that we are the domain specific experts for anyone who works in legal and professional services. Our market traction early is strong, with 500+ customers in 54+ markets. But to realize our long term vision, we need to continue to grow our impact with customers and continue to build a product our customers love, use, and trust, and the Toronto market will be a notable catalyst to that effort.