Harvey

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The platform's own early signals for this company — hard-to-fake, and where one preceded a real raise, the measured lead.

• investor_commentary 1 signal · latest 2023-04-28 predicted the raise 47d early ✓

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• bullish assessment David Friedberg

  I would say Harvey was a first example of this for law firms where the old way was I have a set of lawyers who go and look at contracts and write contracts, that kind of thing. And they basically said, well, I can use AI and verify the outputs with humans and deliver the same thing with fewer humans and deliver it faster at the same quality or near the same quality. And I will disrupt that market.

• bullish assessment SPEAKER_UNKNOWN

  The paradigmatic example is is like a Harvey or something where they get all these law firms on board. So they then get access to their data and then their usage and then they train their own models.

• neutral fact_claim Unattributed

  I think Harvey recently in the past month or so announced something exactly in that vein

• neutral fact_claim Unattributed

  we do see people like Harvey and Ramp and others kind of like experimenting with post-training models for this core loop

• neutral assessment Unattributed

  I think a lot of it is they are post-training open weight models absolutely I still think that's a valuable thing to do I don't think there's kind of like anything wrong with that

• neutral fact_claim Unattributed

  we're seeing a lot whether it's a Harvey or I think it's Ramp build their own models to what extent are they actually building their own models Mike Cannon Brooks had a little ass in said on a show we released today that it's largely kind of respectfully BS and they're fine-tuning open source Chinese models is that true and how do you think about that?

• neutral fact_claim Unattributed

  there was a major validation event, which was when Kirkland came out and said they were going to spend 500 million bucks to build their own technology stack. Yes. Like people were like, oh man, what's that mean for Harvey?

• bullish assessment Unattributed

  Harvey, the legal AI company, released their very first in-house proprietary model. It helps Harvey software take on more tasks that were typically performed by lawyers. It is, Jason, a post-trained open-weight model built on top of Kimi K3. This is sort of what you've been predicting all along, which is application layer companies, companies that have this incredibly valuable expert data. They don't want to turn that over to the anthropics and open AIs of the world. They're going to use it them

• neutral fact_claim Unattributed

  Harvey has forked. I believe it was Quinn. Kimmy. Kimmy K3. To make their own legal AI sovereign, they control it. Yeah. It's on their servers.

• mixed assessment Unattributed

  if you look at Harvey for example I know they're I think leading the category in terms of specialization but I think the large frontier labs are still going to be the dominant providers in the space

• bearish prediction Unattributed

  I wonder if you're looking at something like Harvey today, spending on the side of a building, if they have the right business, the right team, but maybe they blow through the capital and they're like, wow, we spent $10 million on advertising that we could have just put into the product and sales team.

• bearish assessment Unattributed

  Isn't that reminiscent of like living in SF and the .com? I mean, same type of thing. Like, money doesn't mean that you've like won. It'll be interesting to see, I think, at the end of the day where it goes, right?

• bearish criticism Unattributed

  I drove through Times Square, and the side of a building, 40 stories tall, was a Harvey ad. And the ad said, Harvey, $15.5 billion valuation, and then listed Sequoia, blank, blank, and listed 20 VCs, and that was the ad. Do you – but doesn't that remind you of the .com? I was like, are we in San Francisco? What's going on here? This is crazy.

• neutral assessment Unattributed

  Harvey is still – I think the jury is still out on Harvey.

• bullish endorsement Unattributed

  And if it's Harvey or Lagora or the next wave, and I'm literally every hour I'm not in court, and the way you can tell is if at night they're on their laptop with the agent every minute, right, until they go to bed. That's what I think Harry's describing. This is this persistent agent that lives with you.

• bullish prediction Unattributed

  I think she should do 10 times, 20 times more work than before it.

• mixed assessment Unattributed

  let's go back to Harvey Laguerre. The same thing will be true in law. Yes, a lot of the drafting work can be automated, but you're going to have the client meeting, the argument with the other posing counsel. You're not just going to delegate it all to AI if it's significant.

• bullish endorsement Unattributed

  There's no point in having humans do that crap anymore, right?

• bullish prediction Unattributed

  It might be like Harvey and Legora end up doing 95% of what humans used to do. And the best humans are compressed into the five amount, the 5% that moves the needle versus spending weeks on research and weeks on brief writing and weeks on case law from the 1872 when the SS Jonas fell off, sunk off the coast of North Carolina. How does that impact case law in the Northern districts of California? There's no point in having humans do that crap anymore, right?

• neutral assessment Unattributed

  I think on legal, it's about 10%. In other words, I love Harvey and Legora. I love GCAI, right? But the annual subscription per lawyer, it's 10, 12K plus or minus. And these lawyers are getting paid 200K plus. So it's 5%.

• bullish assessment Unattributed

  I now dramatically think these companies are underpriced. If coding is a half a trillion dollar market, and you have two companies like Harvey and Legora, I don't see why there's not a half trillion dollar market in law.

• bearish assessment Unattributed

  the question is like what, like with a billion, like how do you, how do you compete against a billion?

• neutral fact_claim Unattributed

  You've got a law firm that's going with Harvey and Lagora

• neutral fact_claim Unattributed

  the Harveys that have raised a billion

• bullish assessment Unattributed

  we do so much to sort of help our customers not just, you know, implement Harvey, but truly transform their organizations

• bullish assessment Unattributed

  I would say that we do a great job of having sort of a core Harvey brand and vibe, but also each office feels distinct for that market.

• neutral fact_claim Unattributed

  EPD, which is our engineering product design team, went from one location just in San Francisco about 18 months ago to four locations. So San Francisco, Toronto, New York, and Bengaluru, India are sort of the home of our four EPD hubs.

• bullish assessment Unattributed

  a lot of our growth has been around providing our customers with this amazing experience.

• bullish assessment Unattributed

  we're only four years old, but we still have held on to that trust. We still allow folks to have that level of agency and autonomy and the values enable it. They allow you to move quickly. They allow you to make mistakes. And without that, you know, I think that we would not be seeing the success that we have.

• bullish fact_claim Maggie (SPEAKER_00)

  We have a values interview for all candidates when they come on site. The values interview is structured around our three values. So, simplicity, decisiveness, and jobs not finished.

• bullish fact_claim Maggie (SPEAKER_00)

  We are hiring across every team. We are hiring pretty much across every region. We have added many new regions.

• bullish fact_claim Maggie (SPEAKER_00)

  We have over 400 jobs open right now.

• bullish fact_claim Maggie (SPEAKER_00)

  My team went from, I want to say, about 16 to 80 folks in a year in order to support that growth.

• bullish assessment Maggie (SPEAKER_00)

  I definitely wasn't sure it was possible. I wasn't sure we could pull it off. And I think that that's sort of the story of Harvey. You join and you're being asked to do something that you don't actually know is maybe, whether or not it's like maybe possible or possible in that amount of time or possible at the level of quality and execution that you think you should be able to operate. But then you just do it.

• bullish fact_claim Maggie (SPEAKER_00)

  We had plans to get to 16 markets in a year. So the growth that was going to be required to sort of actualize our potential and essentially give our customers the attention they needed created a very unique recruiting challenge in terms of how quickly we were going to have to hyperscale across so many different markets and do it with a level of quality and care while maintaining a really high bar.

• bullish assessment Maggie (SPEAKER_00)

  We have a very upmarket motion and we are super customer centric. And AI transformation is more than just building a great product. But we have essentially this like heavy people motion where for all of our customers, we have essentially an army of go-to-market resources for them, both pre-sale and post-sale.

• bullish prediction Maggie (SPEAKER_00)

  What Harvey was doing in the legal industry, but also in AI. I felt like it was a massive, a massive opportunity.

• bullish assessment Maggie (SPEAKER_00)

  We have so many lawyers or folks who are no longer practicing law, but once were within Harvey in all sorts of roles. Of course, we have an internal legal team, but we also have applied legal researchers who sit in product. We have legal innovation partners who sort of liaise with various, you know, CIOs and the innovation community. We have our legal engineers and legal engineering product specialists who sit on the sales team. And so there's this like deep admiration and respect for, you know,

• bullish fact_claim Maggie (SPEAKER_00)

  We are very close to our customers. We start up every all hands with sort of a customer testimonial. It doesn't matter what team you're on. You're very, very connected to what our customers are trying to do.

• bullish assessment Maggie (SPEAKER_00)

  AI application layer companies in general are trying to transform industries. I think that we attract folks who have a certain customer centricity and an interest and a desire to sort of genuinely sort of reshape something like the legal industry.

• bullish assessment Unattributed

  I love and I know a lot of people love, where you've got this vision and strategy and leadership team that folks can learn a ton from, but you also aren't this big sort of behemoth that's working as a machine, that's not for everybody.

• neutral fact_claim Unattributed

  Harvey is entering teenage years. I would describe it as such because we are not this teeny tiny startup that hasn't found product market fit. And we're also not this fully actualized sort of old, longstanding, mega public company.

• bullish assessment Unattributed

  It sounds like Harvey's, you know, Harvey's culture is open and transparent and vulnerable and supportive and low ego.

• bullish assessment Unattributed

  They speak so openly about how they see the company evolving, how they see the space evolving. After every quarter, he'll put together a quarterly memo for the whole team on what he thinks worked and didn't, et cetera. And so I think sharing that as broadly as we do, it's pretty open. I mean, the company is very open in terms of what the leaders share. We post board decks for the whole company to review after board meetings so they can see what's been shared in those board meetings and host AMAs

• bullish endorsement Unattributed

  What I would say is unique about Winston and Gabe is this quality to be both sort of very like operate at a very high level, strategic, future facing altitude and then get super into the details and be able to do both.

• neutral fact_claim Unattributed

  And now we're talking about hiring 600 people by the end of this year.

• bullish assessment Unattributed

  There is nobody, I would be hard pressed to find anybody at Harvey who feels like they're part of a machine that could be running without them in the same way. I think everybody feels deeply connected to whatever it is that they're working on and knows that, you know, they have an opportunity to make a real impact on whatever, whatever that is.

• bullish assessment Maggie Landers

  The beauty of working at a company like Harvey, both sort of AI native and frankly, a place that values kind of progress over perfection and wants to move quickly, is that it almost doesn't matter what you did three years ago or five years ago or how you did it. I think it's more important that you're sort of actively collaborating and working to figure out what is going to make sense in this new world. And at this moment in time, we're genuinely trying to transform how the legal industry works

• bullish assessment Maggie Landers

  I do think that we've done a good job of understanding kind of what makes somebody successful at Harvey and looking for a lot of those sort of characteristics when we go to market and we bring new people on board. I also think that we have pretty good kind of self-selection in that I think folks know that Harvey is a really ambitious company and that we are looking to be generational in what we build.

• neutral fact_claim Maggie Landers

  we've added over 1,000 employees since I've joined, and we'll likely be about 2,000 employees before the end of this calendar year, which is insane. More than 70% of the company started after January 1st of this year.

• bullish assessment Maggie Landers

  Not just the valuation, but the company growth, the customer growth, our growth, I think our product growth. But I would say that we don't take any of it for granted. I don't think there's anyone internally who feels like we've fully made it or actualized our potential.

• neutral fact_claim Katie Kirsch

  Harvey's valuation has been skyrocketing in the past year from $3 billion last February of 2025 to $5 billion in June, $8 billion in October, $11 billion this past March of 2026.

• bullish assessment Maggie Landers

  Transforming the legal industry is very different than trying to transform customer support or build an AI harness or create a model. You're going to do more in a month at Harvey than you would in a quarter somewhere else. There's a lot of experimentation, so you're going to fail more than you're necessarily going to get it right. And so I think the emphasis is on both failing fast and correcting to make something or build something that has never been built before.

• bullish assessment Unattributed

  And then as we look at the vertical AI companies, these are some of the fastest growing companies we're seeing in the private markets, right? Harvey, a bridge, Elise, they are growing faster than any of the precedents ever have in their industry. And, and that's a reflection of the customers recognizing it's not just the model, which we talked about earlier, but how you, how you orchestrate that, how you build the application around it and vertical specific workflows command, uh, command these n

• bullish prediction Unattributed

  for hotels you know some of these boutique hotels you you know they're they're offering to pay up to upwards of 30 for every you know transaction that that that you're able to deliver for them and i'm not saying again we're going to be at 30 but you can see the range these are existing you know business models that that that we can you know boot shop off of in the early days but then what it would what would it be like to take that and extend it to effectively every major industry

• bullish prediction Unattributed

  i'm looking at the you know can we provide so much value that we're on the upper end scale of this the reason why i think that this is possible is very practically you know 50 of the um transaction volume flowing through the platform is is travel alone and you know we all know the the travel industry and and and some of the rates that are that that we've kind of the ota rates are high yeah it's very high

• neutral assessment Unattributed

  those 40 people making money at each line of the stack are really sharing what two and a half percent two percent it depends on where the transaction is coming from so it's a very actually small piece of the pie and um we're not primarily interested in whatever like doing what amex does best and and have the network to do or what uh even even like what what stripe does uh on the internet or or you know some of the underlying uh payment infrastructure do because it's it's such a small piece of th

• bullish assessment Unattributed

  i see a blanket transaction um take rate being being uh enforced across the platform which is just us exchanging you know distribution for for um uh being able to you know um serve products for on behalf of merchants

• bullish assessment Unattributed

  there's over a billion dollars uh flowing through the platform now every year and and you know we're just we're just getting started and and uh honestly we're going at 10 percent day over day so you know you imagine the transaction volume is also compounding at 10 percent day over day right so so that's not just a billion

• bullish fact_claim Unattributed

  50% of our transaction volume that goes through that goes through our platform is due to travel

• bullish fact_claim Unattributed

  we're approaching over a billion dollars a year in transaction volume through the platform on a small user base

• neutral fact_claim Unattributed

  So I guess we got to keep track of this. But yeah, maybe we get to AI a little bit faster.

• bullish prediction Unattributed

  I think you could see easily how that would work into a recursive self-improvement workflow.

• neutral assessment Unattributed

  For now, definitely it's a it's they're aiming it at it's a developer tool. that's going to help you make your whatever your software you're coding faster, more efficient, more reliable one day.

• neutral fact_claim Unattributed

  Case Text was launched with OpenAI and is powering co-counsel now for Thomson Reuters, right? And Case Text was sitting at like $30, $35 million of ARR and hitting profitability three years ago and not having to spend all that money getting clients.

• bearish prediction Unattributed

  Harvey today, spending on the side of a building, if they have the right business, the right team, but maybe they blow through the capital and they're like, wow, we spent $10 million on advertising that we could have just put into the product and sales team.

• neutral assessment Unattributed

  I think, money doesn't mean that you've, like, won.

• neutral fact_claim Unattributed

  the side of a building, 40 stories tall, was a Harvey ad. And the ad said, Harvey, $15.5 billion valuation.

• neutral assessment Unattributed

  Harvey is still, I think that the jury's still out on Harvey.

• bullish fact_claim Unattributed

  Savvy Wealth announced their $100 million round today. And what they're doing for advisors is exactly that. People thought, well, wealth managers are going to go away. I've never believed that. I think people crave that personal one-on-one attention. But these wealth managers are made 10 times better. And the numbers they're giving us that we have checked is they're getting 19 hours of time back in their week, every week, to do what they want to do most, which is serve clients. And so by doing t

• neutral fact_claim Unattributed

  I think the companies that they've invested in, like Harvey, I think they may have seeded it. But Sequoia led the A, and I think another big firm did the Series B.

• bullish assessment Alex Wilhelm

  First up, Harvey AI. We talked about earlier how AI has seen a lot of promise in the developer space. Well, also in the legal space. What does a lot of writing and ingesting the documents? The legal profession. Ergo, AI is going to be a hot fit. Harvey AI reached 10 million ARR, I think it was last December. Don't know how big it is today. But a lot of investors at least can be very, very excited about what it is building. So I presume it's in quick growth this year as well.

• bullish assessment Alex Wilhelm

  And then finally, Harvey. It's the only vertical AI company on the list, but I was going back through a list of them, and Harvey said that it had tripled ARR in, like, the first couple quarters of this year. So to me, that is indicative of a company that has managed to take a new technology to an old vertical and crack the ARR code.

• neutral fact_claim Unattributed

  when we go into deals and things like that, especially with law firms, open AI doesn't come up very much, right? Copilot doesn't. But some of the law firms use this, but it's really like, we need a legal technology vendor because this is such a vertical industry.

• neutral fact_claim Unattributed

  we actually historically haven't had a big forward deployed motion. And so pretty much a hundred percent of our platform is things that we have built that we are selling to every customer.

• bullish prediction Unattributed

  I imagine that's going to be similar of what happens with these in-house legal departments. Most of the, how do you optimize your legal spend is not going to be you deploy 10,000 super smart legal agents. It's going to be all the process management and the measurement connecting with law firms and things like that. And so I think that's the part where we don't see too many competitors working on that.

• bullish assessment Unattributed

  change management, the training, ways to deliver these services in new ways. And so that part feels like, you know, that's very differentiated. The horizontal players won't build that.

• bullish assessment Unattributed

  we don't see the kind of the value we provide as a company as long-term the individual assistant, but this creates friction as you want to like sell into these organizations. But eventually what we need to provide and is our value prop that I think will be very different than what the foundation models provide is like, what we really need to sell to law firms is here is how you create a more profitable law firm.

• bullish assessment Unattributed

  I think for us, the interesting question is figuring out how to balance these parties. And so one of the big problems we want to solve is there is inherent tension of selling to both sides of this marketplace. And what we're starting to figure out with law firms and their clients is the ideal win here is we can find a model where for law firms, we can make them more profitable on this platform and for their clients, they can also benefit. And I think sometimes when people look at this, they say,

• bullish fact_claim Unattributed

  we actually started outside the US. And so we worked with a lot of the large European law firms. Now we're in over 50 of the AMLA 100. So kind of the top 100 firms and kind of a combination of a lot of the really large US ones, and then a lot of the really large international ones. Mid-market is growing pretty quickly. And so we're starting to sell to smaller law firms and then enterprise kind of the clients of these law firms, private equity and fortune 500 is also growing pretty quickly.

• bullish fact_claim Unattributed

  the good news is that growth has been really, really impressive at the company. You guys scaled from, I think it was 50 million ARR kind of at the end of last year, up to 100 million ARR this August. And I know you guys have, I think around 500 law firms that are clients.

• bullish assessment Unattributed

  I would think of the problem we're solving and the model here is, what are all the industries where you have advisors to companies and the big technical problem that you need to solve is as a company, I need to share my sensitive data with this advisor so they can operate on that data. And this is investment banking, consulting, tax, audit, HR compliance, maybe insurance a bit. And so I think this expands to kind of a bunch of these different industries.

• bullish fact_claim Unattributed

  Yeah, we're actually already doing this in some adjacent industries. And so we do this for tax, for example.

• bullish prediction Unattributed

  what the clients eventually are going to want is I have one legal model and it won't probably be a single LLM. It'll be some complicated LLM system that has access to all of my company's legal data. And it connects to all of my different law firms. And it can learn from the work that all of my law firms and eventually professional service providers are doing for me.

• neutral fact_claim Unattributed

  I think it was in May of this year, you guys added models from Anthropic and Alphabet to the product, kind of giving yourself a multimodal approach to the market.

• neutral fact_claim Unattributed

  we've been doing all these partnerships with iManage, Netdocs, kind of the document management systems of the law firms... we're fully eyes off. We never use any of our client data... the infrastructure we need to build for law firms is how do they partition all of that data... we're starting to have some of those conversations.

• neutral fact_claim Gabriel Pereyra

  we're starting to work with, for example, the Supreme Court in Singapore.

• neutral fact_claim Gabriel Pereyra

  the core business now is more corporate law. And that's where the challenges are much more difficult because most of that data is not public, right? If you think of what these very large law firms are doing for corporations, it's, I have a massive litigation, I want to do a very large acquisition. Most of the data you're working there is very sensitive client data that actually never goes into the public models. And so a lot of that is missing. And then the thing that you mentioned we did with O

• bullish assessment Gabe Pereira

  what we're seeing increasingly is when these large private equity firms or enterprises buy Harvey, they're starting to ask their law firms to also buy it so they can work together. And so I think we're starting to see a bit of this network effect from that.

• neutral fact_claim Gabe Pereira

  one of the massive challenge that these large law firms have is how do you manage all of these different client projects? And so if you're one of these large law firms, you're doing tens of thousands of client matters. You have millions of historical client matters and you need to make sure all that data is separate. And so there's a massive part of the product that I think doesn't get seen as much is all of the governance and admin controls you need.

• neutral fact_claim Gabe Pereira

  I think the big challenge for legal was there didn't exist this kind of single workspace where you could work on these client matters. And so a lot of what we've been building in the past three years is how do we build a single workspace where either a lawyer or an agent could perform a client matter, whether it's a litigation, an M&A, end to end.

• bullish assessment Alex

  You have heard of this company. It's worth a lot of money. It's growing very quickly.

• mixed assessment Chamath Palihapitiya

  legal super wizard for law firms yeah and my partners and i were debating it and what we thought of was well how much do you pay out of the 800 or thousand dollars an hour that you charge to harvey.ai maybe you're willing to pay five percent or ten percent but then the reality is that one of the most powerful things it does is is able to go into westlaw find all these cases and say yeah this is germane to the thing that you're working on right now that's a very useful thing but the n plus first

1. 2028-03-31 What Harvey was doing in the legal industry, but also in AI. I felt like it was a massive, a massive opportunity. · Prediction · confirmed
2. 2026-09-09 unknown · $550M

VentureSignalScore 80.8/100 for harvey, composed from 2 of 4 components (emerging formula), discounted ×0.85 for 50% signal coverage