Authorized AI won’t sound just like the sexiest class in Silicon Valley, but Harvey‘s CEO Winston Weinberg has captured the eye of just about each top-tier investor within the Valley. The corporate’s backers learn like a who’s who of enterprise 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 firm’s valuation has skyrocketed from $3 billion in February 2025 to $5 billion in June to, in late October, $8 billion — an increase that displays each the bonkers numbers beings assigned to AI firms by their personal traders and Harvey’s means to win over main legislation corporations and company authorized departments. In truth, the startup now claims 235 shoppers throughout 63 nations, together with a majority of the highest 10 U.S. legislation corporations; it additionally says it surpassed $100 million in annual recurring income as of August.
We talked with Weinberg for this week’s StrictlyVC Obtain podcast to ask about his wild trip to this point. Throughout that chat, he shared how a chilly e-mail despatched a couple of summers in the past to Sam Altman modified all the pieces, why he believes attorneys will profit fairly than undergo from AI (natch), and the way Harvey is tackling the technically complicated problem of constructing a very multiplayer platform — the place in-house attorneys can safely chat with outdoors stakeholders, for instance — that navigates moral partitions and knowledge permissioning throughout dozens of nations.
This interview has been edited evenly for size. For the complete monty, check out the podcast.
You began as a first-year affiliate at O’Melveny & Myers. What was the second you realized AI might rework authorized work?
So my co-founder was working at Meta on the time; he was additionally my roommate. He was exhibiting me GPT-3, and at first, I swear to God, the principle use case I had for it was operating a Dungeons and Dragons sport with mates in LA. Then I used to be assigned to this landlord-tenant case at O’Melveny, and I didn’t know something about landlord-tenant legislation. I began utilizing GPT-3 to work on it.
My co-founder Gabe [Pereyra] and I found out we might do chain-of-thought prompting earlier than that was actually a factor. We created this tremendous lengthy chain-of-thought immediate over California landlord-tenant statutes. We grabbed 100 questions from r/legaladvice [on Reddit] and ran that immediate over them, then gave the question-answer pairs to 3 landlord-tenant attorneys with out saying something about AI. We simply mentioned, ‘A possible buyer requested this query, right here’s the reply—would you make any edits or would you ship this as is?’ On 86 of the 100 samples, two out of three attorneys or extra mentioned they might ship it with zero edits. That was the second the place we had been like, wow, this complete business might be remodeled by this expertise.
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What occurred subsequent?
We chilly emailed Sam Altman and Jason Kwon, who was the overall counsel at OpenAI. We figured we needed to e-mail a lawyer as a result of in any other case the particular person wouldn’t know if the outputs had been proper. On the morning of July 4th at 10am — I bear in mind this particularly as a result of it was July 4th — we acquired on a name with them and sort of the remainder of the C-suite at OpenAI, and we made our pitch.
Did they write a test instantly?
Yeah. It’s the OpenAI Startup Fund [they are the second-largest investor in Harvey]. OpenAI launched us to our angel traders on the time, Sarah Guo and Elad Gil, after which all the pieces else from there we had been doing ourselves. I truly didn’t have any mates that labored in tech. I didn’t develop up in San Francisco. I didn’t know who the highest VCs had been. I didn’t perceive the way you’re imagined to fundraise. This was all simply internet new to me.
For somebody who wasn’t aware of the VC scene, you’ve raised some huge cash. What enabled you to lift a lot?
I would say one thing the VC group won’t love, however I strongly consider that one of the simplest ways to lift cash is to simply ensure that your organization is doing tremendous properly. I believe there’s quite a lot of recommendation on the market about networking, however to me, crucial factor is to spend nearly the complete time on your online business after which discover VCs that wish to try this with you. You might want to discover a couple of companions that you just suppose are going to go the gap with you. 99% of your time, deal with the enterprise going properly, after which spend time looking for a couple of of us that you just actually suppose you may associate with and that shall be there for you for the long term.
You hit $100 million in ARR in August. With round 400 workers, how shut are you to break-even?
Compute prices are costlier for us than quite a lot of different issues. We’re working in additional than 60 nations with knowledge residency legal guidelines in all of them. For a very long time, should you used a number of fashions in your product, you had to purchase a bucket of compute — a minimal threshold — in each single a kind of nations, even should you didn’t have sufficient shoppers but to assist that value.
Germany and Australia have extremely strict knowledge processing legal guidelines. You can’t ship monetary knowledge outdoors of these nations. We’d arrange Azure or AWS situations in each single a kind of nations, however we’d solely use them to shut three or 4 giant shoppers. Our margins look superb on a token foundation, however they’re worse as a result of we’ve to spend a lot on upfront compute throughout so many jurisdictions. That can get solved over time.
Inform us about your gross sales course of. How are you increasing globally?
Originally of this 12 months, about 4% of our income was from corporates and 96% from legislation corporations. Proper now, 33% of our income is from corporates, and my intestine is by the top of the 12 months, that appears nearer to 40%.
To start with, we’d take public litigation briefs from Pacer, discover the associate that wrote it, put them into Harvey, and present them how they might argue in opposition to their very own temporary. That acquired large consideration as a result of it was related to what they only did.
However what was attention-grabbing is as soon as we acquired adoption at legislation corporations, the legislation corporations themselves would assist us pitch to corporates. A agency like Latham will introduce Harvey to shoppers and say, “Hey, do you know that is how we are able to use AI to do XYZ?” So what began taking place was legislation corporations would truly assist us promote to corporates as a result of they wish to collaborate within the system.
You seek advice from this as “multiplayer.” Are you able to expound on this a a rising space of focus?
It is a big drawback. You’ve seen bulletins from OpenAI and Microsoft about shared threads and firm reminiscence. That’s arduous — you must get the permissioning proper so brokers can entry the correct techniques. However you’re solely fixing it for one entity at a time.
The secondary drawback we’ve is: how do you clear up that for a corporation plus all its legislation corporations? You might want to get the permissioning proper internally and externally. There’s an idea in authorized referred to as moral partitions. Take into consideration a legislation agency within the valley that works with 20 VCs. If you happen to’re engaged on a deal for Sequoia but in addition engaged on one other deal for Kleiner Perkins, what occurs should you unintentionally give all the information on the Sequoia deal to Kleiner Perkins? Big, astronomical drawback. We’ve to unravel inside permissioning and exterior permissioning so brokers can work appropriately, and should you get it fallacious, you’re going to have disastrous impacts on the business.
Have you ever solved this?
It’s undoubtedly in course of. We’re doing all the safety and the permissioning first. The primary model of this at scale will in all probability be accomplished in December. The good factor is as a result of such a excessive proportion of our buyer base are already corporates utilizing Harvey, the safety drawback is way simpler as a result of they’ve already gone by safety evaluate.
How are attorneys primarily utilizing Harvey as we speak?
On this order: Primary is drafting. Quantity two is analysis — that’s rising as a result of we simply have a partnership with LexisNexis. And the third is analyze. What I imply by analyze is operating 10 questions over 100,000 paperwork, like what you do in diligence or discovery.
To start with, we had far more transactional use instances — M&A and fund formation. These are nonetheless very talked-about, and we’re constructing modules particularly for these issues. The world that’s rising sooner is litigation, and quite a lot of that’s since you wanted the information earlier than you might do it.
Some critics have mentioned Harvey is only a wrapper for ChatGPT. How do you reply?
The biggest benefit we’ve over time is 2 issues. One, we’re gathering an incredible quantity of workflow knowledge — what are the principle use instances these fashions can truly do? Analysis turns into a reasonably robust moat as a result of how do you consider the standard of a merger settlement? That turns into actually arduous. It’s a must to arrange analysis frameworks and agentic techniques that may self-eval all of the completely different steps.
The second strongest moat is our product is turning into very strongly multiplayer. This business has two sides — suppliers of authorized providers and shoppers. You might want to construct a platform that’s in between each. To date, I haven’t seen a competitor doing that. We’ve rivals doing what we do for legislation corporations, and rivals doing what we do for in-house, however I haven’t seen somebody construct a very multiplayer platform.
When it comes to the “ChatGPT wrapper” criticism — for 2023 and 2024, quite a lot of the ability behind the product is truthfully the mannequin plus front-end work that makes the UI and UX simpler. However should you’re attempting to construct one thing the place I’ve 100,000 paperwork on this knowledge room, 5,000 emails about this M&A, all these completely different statutes and codes, and I need a system the place I can ask questions over all of these items mixed with excessive accuracy — that’s the holy grail. We’ve created all of the items, and what we’ve been constructing for the previous couple months is pulling that collectively.
What’s your online business mannequin?
Proper now it’s largely seats, however we’re shifting to extra outcome-based pricing because the workflows get extra complicated. You wish to do each. You need outcome-based pricing for very small issues which you could guarantee have the very same stage of accuracy as a human, or higher, with very excessive pace. However the actuality is you’re going to need a lawyer within the loop for a lot of labor.
For at the least the following 12 months or two, it’s a productiveness suite bought seat-based and multiplayer between legislation corporations and their in-house groups. Slowly over time, we’ll construct extra consumption-based workflows because the techniques get higher and extra correct than people in some areas. But it surely’s not going to be such as you automate a whole M&A — it’s going to be particular items of diligence the place you may have disclosure brokers automate the primary go, then have attorneys leap in and do the remainder.
You talked about to us earlier that penetration is de facto low in authorized. How low?
What proportion of the attorneys on Earth are utilizing Harvey proper now? It’s a brilliant low proportion. There are 8 or 9 million attorneys on Earth. However the extra attention-grabbing level is we’re unbelievably early innings on how complicated of labor these techniques can do. They’re very useful and persons are getting unimaginable ROI, but when you consider what proportion of authorized work can these techniques do as we speak versus what I believe it will possibly do within the subsequent 5 years — it’s a lot decrease.
Take into consideration the use case as, what’s the worth per token. The authorized charges for a merger might simply be tens of hundreds of thousands of {dollars}. The artifact you might have after that merger is a merger settlement and an SPA — possibly 200 pages complete. What’s the worth per token on that doc that required $20 million or $30 million of authorized charges to generate? These are the sorts of use instances the place, after I say we’re at extremely low penetration, it’s that we aren’t on the level the place you are able to do one thing like that. And the worth of with the ability to try this precisely is extremely excessive.
What occurs to junior attorneys who’re now not getting the apprenticeship they could have had previously?
I care about this doubtlessly greater than the rest on the firm as a result of I used to be a junior lawyer very just lately. The purpose of legislation corporations within the subsequent 5 to 10 years is: how briskly are you able to prepare the very best companions? I believe proper now, that’s partially the purpose, however partially the purpose is we rent armies of associates and invoice them out rather a lot. Whether or not it’s as a result of issues develop into outcome-based pricing or as a result of companions can cost extra if AI techniques can’t do what they do, crucial factor financially for a legislation agency is to be sure you’re hiring, coaching, and growing attorneys that get to being a associate as quick as humanly doable.
If you happen to can construct instruments that may do the primary go of an M&A, that could be a one-on-one tutor for a junior affiliate. We work with quite a lot of legislation colleges. You may think about sooner or later you might have an AI merger that you just do in Harvey — the system’s educating you, providing you with real-time suggestions. That’s an unimaginable coaching system. If you happen to can construct techniques that may truly do quite a lot of the duties, there’s no cause you couldn’t flip that into the most effective training platforms doable.
Along with your valuation leaping from $3 billion to $8 billion in lower than a 12 months, what are your plans for future fundraising?
Fundraising giant rounds is just not one thing we’ve deliberate anytime quickly. We don’t want that a lot cash, and we aren’t burning a loopy quantity. The rationale I did quite a lot of fundraising this 12 months is there are analysis instructions which can be going to require quite a lot of compute, and we wished to arrange ourselves for that. When it comes to public markets, that’s undoubtedly what we’re concerned about long run. I can’t provide you with something near a timeline, however we’re .
