Legal AI might not sound like the sexiest category in Silicon Valley, but Harvey‘s CEO Winston Weinberg has captured the attention of virtually every top-tier investor in the Valley. The company’s cap table reads like a who’s who of venture capital: the OpenAI Startup Fund (its first institutional investor), Sequoia Capital, Kleiner Perkins, Elad Gil, Google Ventures, Coatue, and most recently, Andreessen Horowitz. The San Francisco-based company’s valuation skyrocketed from $3 billion in February 2025 to $5 billion in June to $8 billion in late October — a rise that reflects both the bonkers price tags awarded to AI companies and Harvey’s ability to win over major law firms and corporate legal departments. In fact, the startup now claims 700 clients across 63 countries, including a majority of the top 10 U.S. law firms. It also says it surpassed <head>00 million in annual recurring revenue as of August. TechCrunch spoke with Weinberg for this week’s StrictlyVC Download podcast to ask about the wild ride that he and co-founder Gabe Pereyra have been on so far. During that chat, he shared how a cold email sent a few summers ago to Sam Altman changed everything; why he believes lawyers will benefit rather than suffer from AI; and how Harvey is tackling the technically complex challenge of building a truly multiplayer platform that navigates ethical walls and data permissioning across dozens of countries. This interview has been edited lightly for length. For the full monty, check out the podcast. You started as a first-year associate at O’Melveny & Myers. When did you realize AI could transform legal work? So my co-founder was working at Meta at the time; he was also my roommate. He was showing me GPT-3, and in the beginning, I swear to God, the main use case I had for it was running a Dungeons and Dragons game with friends in LA. Then I was assigned to this landlord-tenant case at O’Melveny, and I didn’t know anything about landlord-tenant law. I started using GPT-3 to work on it. Techcrunch event San Francisco | October 13-15, 2026 My co-founder Gabe and I figured out we could do chain-of-thought prompting before that was really a thing. We created this super long chain-of-thought prompt over California landlord-tenant statutes. We grabbed 100 questions from r/legaladvice [on Reddit] and ran that prompt over them, then gave the question-answer pairs to three landlord-tenant attorneys without saying anything about AI. We just said, “A potential customer asked this question, here’s the answer — would you make any edits or would you send this as is?” On 86 of the 100 samples, two out of three attorneys or more said they would send it with zero edits. That was the moment when we were like, wow, this entire industry can be transformed by this technology. What happened next? We cold-emailed Sam Altman and Jason Kwon, who was the general counsel at OpenAI. We figured we had to email a lawyer because otherwise the person wouldn’t know if the outputs were right. On the morning of July 4 at 10 a.m. — I remember this specifically because it was July 4 — we got on a call with them and kind of the rest of the C-suite at OpenAI, and we made our pitch. Did they write a check right away? Yeah. It’s the OpenAI Startup Fund [they are the second-largest investor in Harvey]. OpenAI introduced us to our angel investors at the time, Sarah Guo and Elad Gil, and then everything else from there we were doing ourselves. I actually didn’t have any friends that worked in tech. I didn’t grow up in San Francisco. I didn’t know who the top VCs were. I didn’t understand how you’re supposed to fundraise. This was all just net new to me. For someone who wasn’t familiar with the VC scene, you’ve raised a lot of money. What enabled you to raise so much? I might say something the VC community might not love, but I strongly believe that the best way to raise money is to just make sure your company is doing super well. I think there’s a lot of advice out there about networking, but to me, the most important thing is to spend almost the entire time on your business, and then find VCs who want to do that with you. You need to find a few partners who you think are going to go the distance with you. So, 99% of your time, focus on the business going well, and then spend time trying to find a few folks who you really think you can partner with and who will be there for you for the long run. You hit <head>00 million in ARR in August. With around 400 employees, how close are you to break-even? Compute costs are more expensive for us than a lot of other things. We’re operating in more than 60 countries with data residency laws in all of them. For a long time, if you used multiple models in your product, you had to buy a bucket of compute — a minimum threshold — in every single one of those countries, even if you didn’t have enough clients yet to support that cost.