Harvey, every mention
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tap a year for its mentions
every year anyone Kimberly Tan 22Alex Rampell 10Joe Schmidt 4Jen Kha 4Gavin Baker 4David George 4Anish Acharya 3Russ Fraden 1Matt Bornstein 1Elena Burger 1
Verbatim, from the transcripts: the passages where Harvey comes up
Why Investors Are Rethinking Everything for the AI Era
- ▶ 7:18 Jen Kha Our legal counsel, uh, says to us often, it's like, I love Harvey.
- ▶ 23:52 David George And then, you know, it's like one of the things that I said about Harvey Overtime as an example, right? 4 times in the scene
Why AI Demand Is Outrunning Compute Supply
- ▶ 53:01 Gavin Baker I think the best broad instantiation of that today, outside of GrokBot, outside of Cursor, outside of, you know, like Harvey's done some cool things. 4 times in the scene
The State of AI: Models, Moats, and the Consumer Renaissance
- ▶ 9:36 Anish Acharya I know Harvey's had some great results with this as well. 2 times in the scene
- ▶ 14:46 Anish Acharya But you really need Harvey to turn that into an economic outcome for the legal industry.
Lighthouse or Landgrab? How to Pick Your AI Sales Strategy
- ▶ 13:30 Elena Burger I know in the piece you talk about Hebea and Harvey as, as classic lighthouse examples, and then Stutt and Decagon as, as land grab.
- ▶ 15:41 Joe Schmidt You know, another example on the, on the lighthouse side would be, you know, we, we highlight Harvey in, in our article, um, and they just did a fantastic job of winning the right law firms for this very new, very, you know, theoretically… 4 times in the scene
How Open Source Became AI's Backbone | Inferact with a16z
- ▶ 7:39 Matt Bornstein This is what sort of Decagon and Harvey are in the process of doing now.
AI Markets: Deep Dive with a16z's David George
The AI Opportunity that goes beyond Models
- ▶ 17:13 David Haber Most of what you probably heard are around companies like Harvey, you know, serving the defense and the corporate side.
- ▶ 37:09 Alex Rampell I might love Harvey. 2 times in the scene
- ▶ 46:38 Alex Rampell Like Vlex could have sold their data to Harvey.
The $700 Billion AI Productivity Problem No One's Talking About
- ▶ 21:00 Alex Rampell So, you know, part of it is if I'm trying to figure out like, okay, there's a product called Harvey, a lot of people love Harvey, and it seems to make people a lot more productive, but 7 times in the scene
- ▶ 41:05 Russ Fraden How do we help them use cursor more effectively, Harvey more effectively?
How Scale AI is Pioneering the Future of Work
- ▶ 4:20 Ben Scharfstein And they, you know, look to partners like scale and to many others, you know, there's these kind of vertically integrated, whether it's Harvey, Decagon, Sierra, and all those people as well to say,
Agents, Lawyers, and LLMs
- ▶ 0:13 unnamed speaker We really want law firms to collaborate with their clients inside of Harvey and inside with Harvey's agents.
- ▶ 0:27 unnamed speaker I lead product at Harvey. 3 times in the scene
- ▶ 1:05 Kimberly Tan Maybe for people who aren't familiar in the audience or people who are listening online, what exactly does Harvey do? 4 times in the scene
- ▶ 1:27 Kimberly Tan And before we get like just a little bit deeper into the practice of building applied AI, are there like specific use cases that Harvey tackles the most knowing that there are a lot of different workflows one could theoretically do for… 3 times in the scene
- ▶ 3:07 Kimberly Tan I'm curious, like what has Harvey seen in that regard? 5 times in the scene
- ▶ 7:47 unnamed speaker Like Harvey gives 30%, 40% of their time back because it really helps them automate that, you know, mundane rote work. 2 times in the scene
- ▶ 10:16 unnamed speaker Um, you know, we, we started, uh, you know, a seat based model. 2 times in the scene
- ▶ 11:15 unnamed speaker Yeah, so our utilization has grown from 40% earlier last year to 70% now. 3 times in the scene
- ▶ 13:36 unnamed speaker And so in general, I think it would be a disservice to say, oh, only Harvey, uh, only lawyers can use the Harvey and be, uh, and take advantage of it in, inside of this transaction. 3 times in the scene
- ▶ 17:16 unnamed speaker So by default, all our paperwork, everything, you know, doesn't allow Harvey certainly not to even train that data, but people at Harvey can't even look at the data. 3 times in the scene
- ▶ 19:51 unnamed speaker So ultimately like one of the main principles is we want Harvey to feel like a coworker and not just a, 3 times in the scene
- ▶ 21:48 unnamed speaker You need humans, uh, you know, unique data sets where, um, if, if we were just like, Hey, you know, draft this disclosure schedule and it, and Harvey did it, no one would trust it because they had no idea what actually went into creating… 2 times in the scene
- ▶ 26:10 unnamed speaker So, as I mentioned previously, Harvey is, consists of, you know, hundreds of different molecules, using agentic or compound AI system to produce the output.
- ▶ 29:38 unnamed speaker Um, and so, and I think part of the challenge here is how do you communicate to customers that Harvey is good or accurate or doesn't hallucinate or whatever it is. 2 times in the scene
- ▶ 33:42 Kimberly Tan Has Harvey built its own foundation model or do you guys have any plans to? 4 times in the scene
- ▶ 34:30 Kimberly Tan So you guys don't want to build your own foundation model. 6 times in the scene
- ▶ 38:34 unnamed speaker We haven't really seen, even, even in leading enterprises and not just law firms, we haven't really seen workflow specific adoption of AI in the way that Harvey is trying to, trying to push.
How AI Will Transform Accounting: A $100B Opportunity Explained
- ▶ 4:35 unnamed speaker So, you know, in, in legal AI, there's this company called Harvey that many of the people listening to this will be familiar with, um, has grown really rapidly. 2 times in the scene