people here in this conference said we were the most likely company to fail.
Okay, let's address that.
It was this time a year ago where there was a vote and they said it wasn't to fail. They said they wanted to short you guys.
Yeah.
Well, here I am sitting here still and we're doing better than most companies ever performing. So,
people would have lost money on that trade.
Yeah. And I would bet the same this year. If you guys short us, you're going to lose more money next year.
We've obviously heard from a lot of people today. You know, it's such a seismic event. And you know, Arvind, I want to kind of just bring up the tweet that you put out a couple of hours ago, basically after Jensen announced that he had resigned, because you're someone who obviously, you know, they're an investor in Perplexity, but you know, you're someone who also has dealt with him a lot from the business side and, you know, I think are quite close to him. So, you know, the tweet that you put out, you know, thank you Jensen Huang for 33 years of bold leadership. You built a small startup into America's most valuable company with relentless improvement. Your grit and perseverance should always be remembered. Your personal generosity with time and advice to founders like me has secured a bright future for America and AI. I mean, can you kind of give us a sense as to like what you're thinking today and you know, what's I imagine kind of a chaotic and unusual day in the world of AI?
Yeah, so Perplexity and Nvidia have been working together for many years now.
Are they one of your largest investors?
They're one of our largest investors. Yes. And it's one of the greatest technology companies in the history of America. And we're, you know, everybody here is using Nvidia compute, Nvidia GPUs, Nvidia libraries. And you know, before any of this controversy, like no, there's no doubt about the history of innovation that the company has done. And Jensen is one of the greatest founders ever, right? And part of that is his relentless grit, determination, constantly looking to build the next thing, not being satisfied with where he is. And those are all great traits for any founder to make it. And just like me, I'm sure every founder here wants to build a trillion dollar company. And he's done it from, you know, having a breakfast or lunch with his co-founders at Denny's to actually like building the world's most valuable company. That's the sort of story that everybody gets inspired by. And like, I feel like in amidst all this noise, we should remember to, you know, take the right lesson of like what relentlessness, grit, determination, and long-term thinking can actually help us build.
Yeah. I mean, can you talk more specifically about you guys and what Jensen was able to kind of bring to Perplexity to build you guys to where you are today?
So, we collaborated with them on a lot of inference libraries. You know, starting from TensorRT and then NVIDIA Dynamo. A lot of our inference engineers have collaborated with inference engineers at Nvidia. We've open sourced a lot of things together. Obviously, like we've been working with them on Nemotron as part of their coalition program with a few other labs, and Nemotron 350, we contributed a lot of like mid-training data to that, and we're going to continue collaborating with them on Nemotron 4. We've had pretty good conversations with not just Jensen but the whole executive team there, including Colette, and we're going to continue working on a lot more projects.
Have you had the opportunity today? I mean, it's only been a couple of hours to kind of check in with the team there and see how things are functioning at this company and
Yeah, I had a meeting with them even today, so things are going as usual and you know, business has to go on and even now, like the best GPUs to run your inference is Nvidia and best GPUs to run your training is Nvidia and none of that stops. So we just have to continue building the future.
Yeah. And last question on this. I mean, have they said anything to you as a major partner to kind of let you know what continuity looks like and kind of let you know that like while we deal with this fairly insane unprecedented situation, like the relationship you have with Nvidia will be unchanged in many ways.
They built a phenomenal foundation. So, their founder has set them up so well for the future.
So, we need to continue expanding on that and that's what we're focused on. So they are
Okay, and then last question. I mean, have you at all had a chance to talk to Jensen in the last couple of days?
Not really. Yeah. Not a lot going on there. Okay. So let's talk about Perplexity. You know, I remember first coming across you guys actually a colleague of mine at the journal who maybe is here tonight, you know, kind of introduced us all to this idea of an answers engine. It's not a search engine. And it's basically you guys were the first ones to use LLMs as a way to get the answers to the questions you had that previously were like whatever the 20 blue links on a page, and that kind of confined you guys at least in my head to being a consumer company. You guys were consumer in the way that Google is the greatest consumer internet company maybe ever made. Is that a fair way to describe what Perplexity is today? Are you still a consumer AI focused company?
Perplexity is for anybody who wants world-class research and accurate AI. That is everybody using Microsoft Word. Is Word a consumer product or enterprise?
Well, that's the thing. Every great consumer product, when it goes up market in the enterprise, it has this advantage that it's already a known brand and it solves a real practical utility problem. What Perplexity solved is the utility of like accurate AI. When we started, we had a bunch of investors who are now working at like big tech companies actually who actually told me that it's a bad idea to give accurate answers because people actually like it if AI makes mistakes and AI hallucinates because people actually find that entertaining, and that was true a lot of how the
Your investors told you AI is
One of my, not one of my investors, is very well regarded, told me that, obviously not going to name who, but you know, one of his arguments was that it's actually a good idea to make AIs hallucinate because, you know, it's entertaining to watch AIs make mistakes and share that and screenshot it and it goes viral on Twitter and that'll give you a lot of new users.
And obviously, like we did the opposite of that and we've been pretty good too, right? And I think fundamentally the problem really solved is getting AI to be accurate. And obviously that's immediately realizable in the form of an answer engine. But you can keep building on that accuracy foundation for deep research, browsing agents. Every form of agentic action is search. You're searching for the right tool. You're searching for the right file. You're searching for the paragraph within the file. You're figuring out which files to use in a big repository of code. You're figuring out how to like orchestrate different models, different connectors, how to put it all together to a final report or an answer or a web app or an artifact. Each of these individual actions is picking something in a large search space.
So with good accurate AI, you can build the best possible agents. And building safe agents is also the same problem. You just have to be accurate. And so we're building on the foundations we started in 2022 and that's allowed us to not just build an answer engine but go beyond that to building a deep research experience that's world-class, state-of-the-art browsing agents last year, sandbox cloud-based agents this year, and most recently persistent co-workers in the form of teammates.
Yeah. When you look at the revenue for Perplexity and like the mix, tell me when I'm wrong here, but you guys sort of began with subscription based, right? People were paying for like the pro version of Perplexity which uses, you know, multiple models, and then you guys I think do some sort of token usage based products now, and I imagine that's kind of part of your shift more towards enterprise customers. Is that you kind of more token based?
Yes, a big part of our revenue growth this year has been coming from consumption based or token based, and we charge for usage based on our computer agent. And every subscription plan gets a certain amount of bootstrap credits. On the $200 a month plan, everybody gets a certain number of credits every month. And so, and we have a credit system for the $20 a month plan as well. But the demand for actually automating a lot of your workflows in an enterprise or a business context is very high that people run out of those credits pretty quickly and are happy to pay for credit based usage. A lot of usage comes from repeat automations. It's not coming from the same user going again and again and chatting one more time and adding to their credit consumption. It's actually coming from them automating a lot of their workflows that they would have otherwise hired a lot of people for: analysts, SEO, marketing, growth marketers, ad campaign management, chief of staff or admin like usage, corporate development, strategy, competitor tracking. These are all like repeat automations that you once set it up and your whole business relies on this. So the revenue is sticky, the net dollar retention is very high. And our job is to actually keep lowering the cost for doing the same task that was more expensive six months ago by continually orchestrating and routing to the best possible model for the job and lowering the price. And we often see that that takes a hit on our usage-based annualized revenue in the short term, but the usage expands enough and then total revenue keeps going up.
What would you say? I mean, what is the main use right now? Like the most amount of use of Perplexity tools is coming from what?
Research, monitoring, automations, almost all forms of knowledge work outside of coding.
We have pretty much a market fit because all of it comes down to like orchestration, routing, and accuracy.
And our harness is really good for that.
Yeah. And SemiAnalysis pointed out like yesterday that
increasing percentage of their AI usage is around persistent agents, right, that they can delegate to like a Slack coworker. And Perplexity has the best harness and product experience around that, and that's because we really own the underlying infrastructure powering these agents. We built our own sandboxes, we built our own model routing, and we host our own models when we delegate to like open weight models that are fine-tuned. And so this is the way in which like we get to be the orchestrator of all possible knowledge work.
Yeah, I saw, you know, you had an exchange with Dylan Patel of SemiAnalysis about this because he was making this case that the reason he loves using Computer, I believe, or Teammates as a harness versus just because I believe the underlying model for them is Anthropic's models, but he just said straight up, which is very Dylan-like, Anthropic is not good at building product. Maybe the technology itself is good, but like they are, when it came to actually developing a useful harness, what you guys have done is so much more effective for what they need. I mean, do you think that's the role for companies like yours now is to just be so much better at building harnesses that there's inherent value just in that and not have to basically let the foundation model companies build the models, but they just suck at harnesses and product and they're just not going to be threatening to you?
We believe in a world of multiple models, right? Just as Anthropic's making great progress, so is Google. Claude is pretty much at frontier quality and OpenAI is behind today, but that's not going to be the case for too many weeks or months. And so as this competition at the model layer arises, the value accrues to the one who can orchestrate all of these in a really solid harness that stays model agnostic, lightweight, so not a lot of hard coding, so you're not building around the limitations of models, you're actually benefiting from progress in the models, and world-class infrastructure. You need to own your own sandboxes. You need to keep it safe. Enterprises need to be able to trust their agents to be running on your platform. It needs to respect role-based access. Agents cannot go rogue inside your sandbox. So all that stuff matters tremendously. Connectors fail a lot in most other agent products, not on ours. So solid connector infrastructure and of course our search advantages, being able to spin up browsers on the sandbox, right? These are all things outside the model that you have to be extremely good at for providing a reliable experience to a demanding organization like SemiAnalysis.
Yeah. So let's actually talk about the progression of your products because I find it very interesting and I'm sure I'm going to mess up the timeline, so just cut in when I get it wrong, but you obviously have your answers engine and then I believe last year you built Comet which is a browser. And I mean I'd love to know an update on usage and your commitment to continuing that, but I think through Comet you guys end up developing Computer which is your kind of
and then from there Teammates come.
So we really recognized that you need to be where users are, which is why we built a browsing agent because most people spend a lot of time on their browser.
But what we realized is people like this conversational interface using things from their phone, being able to delegate their tasks from the phone itself. And for that you actually just have to put the browser on the cloud.
Except like the infrastructure to run everything inside a sandbox and have a coding agent orchestrate the whole thing did not exist when we first launched Comet. It started more towards the end of last year when Opus 4.6 was really, really good. So that's when we took two months or three months off around the time people here in this conference said we were the most likely company to fail.
Okay, let's address that.
